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disambiguation</title> <meta name="description" content="Search results for: word sense disambiguation"> <meta name="keywords" content="word sense disambiguation"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="word sense disambiguation"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 2491</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: word sense disambiguation</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2491</span> A Supervised Approach for Word Sense Disambiguation Based on Arabic Diacritics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alaa%20Alrakaf">Alaa Alrakaf</a>, <a href="https://publications.waset.org/abstracts/search?q=Sk.%20Md.%20Mizanur%20Rahman"> Sk. Md. Mizanur Rahman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Since the last two decades’ Arabic natural language processing (ANLP) has become increasingly much more important. One of the key issues related to ANLP is ambiguity. In Arabic language different pronunciation of one word may have a different meaning. Furthermore, ambiguity also has an impact on the effectiveness and efficiency of Machine Translation (MT). The issue of ambiguity has limited the usefulness and accuracy of the translation from Arabic to English. The lack of Arabic resources makes ambiguity problem more complicated. Additionally, the orthographic level of representation cannot specify the exact meaning of the word. This paper looked at the diacritics of Arabic language and used them to disambiguate a word. The proposed approach of word sense disambiguation used Diacritizer application to Diacritize Arabic text then found the most accurate sense of an ambiguous word using Naïve Bayes Classifier. Our Experimental study proves that using Arabic Diacritics with Naïve Bayes Classifier enhances the accuracy of choosing the appropriate sense by 23% and also decreases the ambiguity in machine translation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arabic%20natural%20language%20processing" title="Arabic natural language processing">Arabic natural language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20translation" title=" machine translation"> machine translation</a>, <a href="https://publications.waset.org/abstracts/search?q=Naive%20bayes%20classifier" title=" Naive bayes classifier"> Naive bayes classifier</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20sense%20disambiguation" title=" word sense disambiguation"> word sense disambiguation</a> </p> <a href="https://publications.waset.org/abstracts/51286/a-supervised-approach-for-word-sense-disambiguation-based-on-arabic-diacritics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51286.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">358</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2490</span> Contextual SenSe Model: Word Sense Disambiguation using Sense and Sense Value of Context Surrounding the Target</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Vishal%20Raj">Vishal Raj</a>, <a href="https://publications.waset.org/abstracts/search?q=Noorhan%20Abbas"> Noorhan Abbas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ambiguity in NLP (Natural language processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential am-biguities. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a novel method to create an affinity matrix to calculate the affinity be-tween any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an al-gorithm to create the sense clusters of tokens using affinity matrix under hierar-chy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contex-tual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and chal-lenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=word%20sense%20disambiguation%20%28wsd%29" title="word sense disambiguation (wsd)">word sense disambiguation (wsd)</a>, <a href="https://publications.waset.org/abstracts/search?q=contextual%20sense%20model%20%28csm%29" title=" contextual sense model (csm)"> contextual sense model (csm)</a>, <a href="https://publications.waset.org/abstracts/search?q=most%20frequent%20sense%20%28mfs%29" title=" most frequent sense (mfs)"> most frequent sense (mfs)</a>, <a href="https://publications.waset.org/abstracts/search?q=part%20of%20speech%20%28pos%29" title=" part of speech (pos)"> part of speech (pos)</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing%20%28nlp%29" title=" natural language processing (nlp)"> natural language processing (nlp)</a>, <a href="https://publications.waset.org/abstracts/search?q=oov%20%28out%20of%20vocabulary%29" title=" oov (out of vocabulary)"> oov (out of vocabulary)</a>, <a href="https://publications.waset.org/abstracts/search?q=lemma_pos%20%28a%20token%20where%20lemma%20and%20pos%20of%20word%20are%20joined%20by%20underscore%29" title=" lemma_pos (a token where lemma and pos of word are joined by underscore)"> lemma_pos (a token where lemma and pos of word are joined by underscore)</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval%20%28ir%29" title=" information retrieval (ir)"> information retrieval (ir)</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20translation%20%28mt%29" title=" machine translation (mt)"> machine translation (mt)</a> </p> <a href="https://publications.waset.org/abstracts/174306/contextual-sense-model-word-sense-disambiguation-using-sense-and-sense-value-of-context-surrounding-the-target" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/174306.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">107</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2489</span> Leveraging Large Language Models to Build a Cutting-Edge French Word Sense Disambiguation Corpus</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mouheb%20Mehdoui">Mouheb Mehdoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Amel%20Fraisse"> Amel Fraisse</a>, <a href="https://publications.waset.org/abstracts/search?q=Mounir%20Zrigui"> Mounir Zrigui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the increasing amount of data circulating over the Web, there is a growing need to develop and deploy tools aimed at unraveling semantic nuances within text or sentences. The challenges in extracting precise meanings arise from the complexity of natural language, while words usually have multiple interpretations depending on the context. The challenge of precisely interpreting words within a given context is what the task of Word Sense Disambiguation meets. It is a very old domain within the area of Natural Language Processing aimed at determining a word’s meaning that it is going to carry in a particular context, hence increasing the correctness of applications processing the language. Numerous linguistic resources are accessible online, including WordNet, thesauri, and dictionaries, enabling exploration of diverse contextual meanings. However, several limitations persist. These include the scarcity of resources for certain languages, a limited number of examples within corpora, and the challenge of accurately detecting the topic or context covered by text, which significantly impacts word sense disambiguation. This paper will discuss the different approaches to WSD and review corpora available for this task. We will contrast these approaches, highlighting the limitations, which will allow us to build a corpus in French, targeted for WSD. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=semantic%20enrichment" title="semantic enrichment">semantic enrichment</a>, <a href="https://publications.waset.org/abstracts/search?q=disambiguation" title=" disambiguation"> disambiguation</a>, <a href="https://publications.waset.org/abstracts/search?q=context%20fusion" title=" context fusion"> context fusion</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing" title=" natural language processing"> natural language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=multilingual%20applications" title=" multilingual applications"> multilingual applications</a> </p> <a href="https://publications.waset.org/abstracts/193871/leveraging-large-language-models-to-build-a-cutting-edge-french-word-sense-disambiguation-corpus" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193871.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">7</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2488</span> Unlocking the Potential of Short Texts with Semantic Enrichment, Disambiguation Techniques, and Context Fusion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mouheb%20Mehdoui">Mouheb Mehdoui</a>, <a href="https://publications.waset.org/abstracts/search?q=Amel%20Fraisse"> Amel Fraisse</a>, <a href="https://publications.waset.org/abstracts/search?q=Mounir%20Zrigui"> Mounir Zrigui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper explores the potential of short texts through semantic enrichment and disambiguation techniques. By employing context fusion, we aim to enhance the comprehension and utility of concise textual information. The methodologies utilized are grounded in recent advancements in natural language processing, which allow for a deeper understanding of semantics within limited text formats. Specifically, topic classification is employed to understand the context of the sentence and assess the relevance of added expressions. Additionally, word sense disambiguation is used to clarify unclear words, replacing them with more precise terms. The implications of this research extend to various applications, including information retrieval and knowledge representation. Ultimately, this work highlights the importance of refining short text processing techniques to unlock their full potential in real-world applications. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=information%20traffic" title="information traffic">information traffic</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20summarization" title=" text summarization"> text summarization</a>, <a href="https://publications.waset.org/abstracts/search?q=word-sense%20disambiguation" title=" word-sense disambiguation"> word-sense disambiguation</a>, <a href="https://publications.waset.org/abstracts/search?q=semantic%20enrichment" title=" semantic enrichment"> semantic enrichment</a>, <a href="https://publications.waset.org/abstracts/search?q=ambiguity%20resolution" title=" ambiguity resolution"> ambiguity resolution</a>, <a href="https://publications.waset.org/abstracts/search?q=short%20text%20enhancement" title=" short text enhancement"> short text enhancement</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20retrieval" title=" information retrieval"> information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=contextual%20understanding" title=" contextual understanding"> contextual understanding</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing" title=" natural language processing"> natural language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=ambiguity" title=" ambiguity"> ambiguity</a> </p> <a href="https://publications.waset.org/abstracts/193872/unlocking-the-potential-of-short-texts-with-semantic-enrichment-disambiguation-techniques-and-context-fusion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/193872.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">8</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2487</span> Author Name Disambiguation for Biomedical Literature</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Parthiban%20Srinivasan">Parthiban Srinivasan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> PubMed provides online access to the National Library of Medicine database (MEDLINE) and other publications, which contain close to 25 million scientific citations from 1865 to the present. There are close to 80 million author name instances in those close to 25 million citations. For any work of literature, a fundamental issue is to identify the individual(s) who wrote it, and conversely, to identify all of the works that belong to a given individual. Due to the lack of universal standards for name information, there are two aspects of name ambiguity: name synonymy (a single author with multiple name representations), and name homonymy (multiple authors sharing the same name representation). In this talk, we present some results from our extensive work in author name disambiguation for PubMed citations. Information will be presented on the effectiveness and shortcomings of different aspects of successful name disambiguation such as parsing, validation, standardization and normalization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=disambiguation" title="disambiguation">disambiguation</a>, <a href="https://publications.waset.org/abstracts/search?q=normalization" title=" normalization"> normalization</a>, <a href="https://publications.waset.org/abstracts/search?q=parsing" title=" parsing"> parsing</a>, <a href="https://publications.waset.org/abstracts/search?q=PubMed" title=" PubMed"> PubMed</a> </p> <a href="https://publications.waset.org/abstracts/39272/author-name-disambiguation-for-biomedical-literature" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/39272.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">300</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2486</span> Accounting as Addressed in the Qur’aan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shahriar%20M.%20Saadullah">Shahriar M. Saadullah</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdul-Quddoos%20Abdul-Basith"> Abdul-Quddoos Abdul-Basith</a>, <a href="https://publications.waset.org/abstracts/search?q=Zaki%20K.%20Abushawish"> Zaki K. Abushawish</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As a part of academic research in Islamic Accounting it is important to know how the word Accounting is discussed in the Qur’aan. This paper identifies and analyzes the word Accounting in the Qur’aan, which is significant to know and understand. The paper uses a methodology of identifying the root word of Accounting Hasaba (حسب) in the Qur’aan with the help of Islam 360 software and analyzes the use of the relevant words derived from the root word. Then the paper attempts to connect the findings to the contemporary Accounting issues. The paper finds that the root word of Accounting Hasaba (حسب) appears in the Qur’aan 109 times but it is only used in the sense Account, Accountable, or Accounting 45 times. These words appear in 44 different verses in the Qur’aan, appearing twice in one of the verses. The paper divides these verses into 8 different themes namely, Day of Accounting, without any Accounting, Accounting of Time, Self-Accounting, Swift in Accounting, Accounting is only with God, Awareness and the Good Accounting, and Heedlessness and the Bad Accounting. The way the words Account, Accounting, and Accountable is discussed in the Qur’aan links to the contemporary accounting issues including Ethics, Agency Theory, and Internal Control. The links discovered in the paper clearly shows the timeless nature of the message of the Qur’aan. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=accounting" title="accounting">accounting</a>, <a href="https://publications.waset.org/abstracts/search?q=contemporary%20accounting%20issues" title=" contemporary accounting issues"> contemporary accounting issues</a>, <a href="https://publications.waset.org/abstracts/search?q=Qur%27aan" title=" Qur'aan"> Qur'aan</a>, <a href="https://publications.waset.org/abstracts/search?q=root%20word%20of%20accounting%20hasaba" title=" root word of accounting hasaba"> root word of accounting hasaba</a> </p> <a href="https://publications.waset.org/abstracts/99304/accounting-as-addressed-in-the-quraan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/99304.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">419</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2485</span> The Implementation of Word Study Wall in an Online English Word Memorization Class</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yidan%20Shao">Yidan Shao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> With the advancement of the economy, technology promotes online teaching, and learning has become one of the common features in the educational field. Meanwhile, the dramatic expansion of the online environment provides opportunities for more learners, including second language learners. A greater command of vocabulary improves students’ learning capacity, and word acquisition and development play a critical role in learning. Furthermore, the Word Wall is an effective tool to improve students’ knowledge of words, which works for a wide range of age groups. Therefore, this study is going to use the Word Wall as an intervention to examine whether it can bring some memorization changes in an online English language class for a second language learner based on the word morphology method. The participant will take ten courses in the experiment as it plans. The findings show that the Word Wall activity plays a slight role in improving word memorizing, but it does affect instant memorization. If longer periods and more comprehensive designs of research can be applied, it is expected to have more value. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=second%20language%20acquisition" title="second language acquisition">second language acquisition</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20morphology" title=" word morphology"> word morphology</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20memorization" title=" word memorization"> word memorization</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20Word%20Wall" title=" the Word Wall"> the Word Wall</a> </p> <a href="https://publications.waset.org/abstracts/157829/the-implementation-of-word-study-wall-in-an-online-english-word-memorization-class" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157829.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">119</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2484</span> Word of Mouth and Its Impact on Marketing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatima%20Naz">Fatima Naz</a>, <a href="https://publications.waset.org/abstracts/search?q=Ayesha%20Tariq"> Ayesha Tariq </a> </p> <p class="card-text"><strong>Abstract:</strong></p> In view of growing of the internet users for e-commerce and taking into account, the emergent impact of word of mouth phenomenon this research has different aims. The aims of this study were built following dissimilar discussion with teachers and colleagues enlightening that word of mouth information for online purchasing do not have the same effect for everybody. Then they were born following dissimilar researchers together with what was already done in previous researches and what was completed. As a result different aims were drawn; the initial aim of this research is to study the attention of the customers in the word of mouth to power their online purchasing activities. The next aim is to analyze the people influenced by the interest of word of mouth. The following aim is to examine the marketing behavior bearing in mind the internet progress and word of mouth, their consideration for word of mouth marketing. In the form of research questions the aims of the study are: 1) How community utilizes and multiplies word of mouth information about online purchasing experience? 2) How communities perceive the word of mouth marketing? 3) How marketers take the word of mouth phenomenon and how they handle it? <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=belief" title="belief">belief</a>, <a href="https://publications.waset.org/abstracts/search?q=power" title=" power"> power</a>, <a href="https://publications.waset.org/abstracts/search?q=inspiration" title=" inspiration"> inspiration</a>, <a href="https://publications.waset.org/abstracts/search?q=self-expression" title=" self-expression"> self-expression</a>, <a href="https://publications.waset.org/abstracts/search?q=positive%20attitude%20to%20online%20marketing" title=" positive attitude to online marketing"> positive attitude to online marketing</a>, <a href="https://publications.waset.org/abstracts/search?q=forwarding%20of%20contents" title=" forwarding of contents"> forwarding of contents</a>, <a href="https://publications.waset.org/abstracts/search?q=purchasing%20decision" title=" purchasing decision"> purchasing decision</a>, <a href="https://publications.waset.org/abstracts/search?q=standard%20marketing" title=" standard marketing"> standard marketing</a> </p> <a href="https://publications.waset.org/abstracts/3172/word-of-mouth-and-its-impact-on-marketing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/3172.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">422</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2483</span> A Word-to-Vector Formulation for Word Representation </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sandra%20Rizkallah">Sandra Rizkallah</a>, <a href="https://publications.waset.org/abstracts/search?q=Amir%20F.%20Atiya"> Amir F. Atiya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work presents a novel word to vector representation that is based on embedding the words into a sphere, whereby the dot product of the corresponding vectors represents the similarity between any two words. Embedding the vectors into a sphere enabled us to take into consideration the antonymity between words, not only the synonymity, because of the suitability to handle the polarity nature of words. For example, a word and its antonym can be represented as a vector and its negative. Moreover, we have managed to extract an adequate vocabulary. The obtained results show that the proposed approach can capture the essence of the language, and can be generalized to estimate a correct similarity of any new pair of words. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing" title="natural language processing">natural language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20to%20vector" title=" word to vector"> word to vector</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20similarity" title=" text similarity"> text similarity</a>, <a href="https://publications.waset.org/abstracts/search?q=text%20mining" title=" text mining"> text mining</a> </p> <a href="https://publications.waset.org/abstracts/81808/a-word-to-vector-formulation-for-word-representation" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81808.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">275</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2482</span> TransDrift: Modeling Word-Embedding Drift Using Transformer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nishtha%20Madaan">Nishtha Madaan</a>, <a href="https://publications.waset.org/abstracts/search?q=Prateek%20Chaudhury"> Prateek Chaudhury</a>, <a href="https://publications.waset.org/abstracts/search?q=Nishant%20Kumar"> Nishant Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Srikanta%20Bedathur"> Srikanta Bedathur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=NLP%20applications" title="NLP applications">NLP applications</a>, <a href="https://publications.waset.org/abstracts/search?q=transformers" title=" transformers"> transformers</a>, <a href="https://publications.waset.org/abstracts/search?q=Word2vec" title=" Word2vec"> Word2vec</a>, <a href="https://publications.waset.org/abstracts/search?q=drift" title=" drift"> drift</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20embeddings" title=" word embeddings"> word embeddings</a> </p> <a href="https://publications.waset.org/abstracts/165423/transdrift-modeling-word-embedding-drift-using-transformer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165423.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">91</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2481</span> Substitutional Inference in Poetry: Word Choice Substitutions Craft Multiple Meanings by Inference</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20Marie%20Hicks">J. Marie Hicks</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The art of the poetic conjoins meaning and symbolism with imagery and rhythm. Perhaps the reader might read this opening sentence as 'The art of the poetic combines meaning and symbolism with imagery and rhythm,' which holds a similar message, but is not quite the same. The reader understands that these factors are combined in this literary form, but to gain a sense of the conjoining of these factors, the reader is forced to consider that these aspects of poetry are not simply combined, but actually adjoin, abut, skirt, or touch in the poetic form. This alternative word choice is an example of substitutional inference. Poetry is, ostensibly, a literary form where language is used precisely or creatively to evoke specific images or emotions for the reader. Often, the reader can predict a coming rhyme or descriptive word choice in a poem, based on previous rhyming pattern or earlier imagery in the poem. However, there are instances when the poet uses an unexpected word choice to create multiple meanings and connections. In these cases, the reader is presented with an unusual phrase or image, requiring that they think about what that image is meant to suggest, and their mind also suggests the word they expected, creating a second, overlying image or meaning. This is what is meant by the term 'substitutional inference.' This is different than simply using a double entendre, a word or phrase that has two meanings, often one complementary and the other disparaging, or one that is innocuous and the other suggestive. In substitutional inference, the poet utilizes an unanticipated word that is either visually or phonetically similar to the expected word, provoking the reader to work to understand the poetic phrase as written, while unconsciously incorporating the meaning of the line as anticipated. In other words, by virtue of a word substitution, an inference of the logical word choice is imparted to the reader, while they are seeking to rationalize the word that was actually used. There is a substitutional inference of meaning created by the alternate word choice. For example, Louise Bogan, 4th Poet Laureate of the United States, used substitutional inference in the form of homonyms, malapropisms, and other unusual word choices in a number of her poems, lending depth and greater complexity, while actively engaging her readers intellectually with her poetry. Substitutional inference not only adds complexity to the potential interpretations of Bogan’s poetry, as well as the poetry of others, but provided a method for writers to infuse additional meanings into their work, thus expressing more information in a compact format. Additionally, this nuancing enriches the poetic experience for the reader, who can enjoy the poem superficially as written, or on a deeper level exploring gradations of meaning. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=poetic%20inference" title="poetic inference">poetic inference</a>, <a href="https://publications.waset.org/abstracts/search?q=poetic%20word%20play" title=" poetic word play"> poetic word play</a>, <a href="https://publications.waset.org/abstracts/search?q=substitutional%20inference" title=" substitutional inference"> substitutional inference</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20substitution" title=" word substitution"> word substitution</a> </p> <a href="https://publications.waset.org/abstracts/52403/substitutional-inference-in-poetry-word-choice-substitutions-craft-multiple-meanings-by-inference" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/52403.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">238</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2480</span> The Connection of the Nibbāna with the Six Sense Bases</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Wattegama%20Subhavi">Wattegama Subhavi </a> </p> <p class="card-text"><strong>Abstract:</strong></p> A being is the working of the six sense bases. The sense bases are the eye, the ear, the nose, the tongue, the body and the mind. Buddhism describes what these sense bases are and how they work. These sense bases can be related to many of the philosophical and psychological teachings of the Buddha. One of the most important teachings of the Buddha is the Four Noble Truths. Buddhism explains that one who needs to attain <em>Nibbāna</em> must understand and realize these Four Noble Truths. These noble truths have a direct connection with the sense bases. The ultimate goal of Buddhism is <em>Nibbāna</em>. But there is no place or a special world called the “<em>Nibbāna</em>”. This paper describes that the noble truths can be identified within one’s own sense bases. The noble truth of suffering occurs within the functioning of the sense bases and the cause of suffering, “craving” operates inside the senses bases and the cessation of suffering, or <em>Nibbāna</em> is also experienced in the Sense Bases. Relevant material will be drawn for this paper directly from the <em>Pāli</em> canonical sources. The major finding is that the first three noble truths can be experienced through the six sense bases. The conclusion derived from the study is that the sense bases have direct relevance to <em>Nibbāna</em>, which is not to be conceived as another place or another dimension, but phenomena that can be experienced through one’s own sense bases, and that the other noble truths are also to be experienced in relation to one’s own sense bases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Buddhism" title="Buddhism">Buddhism</a>, <a href="https://publications.waset.org/abstracts/search?q=Four%20Noble%20Truths" title=" Four Noble Truths"> Four Noble Truths</a>, <a href="https://publications.waset.org/abstracts/search?q=sense%20bases" title=" sense bases"> sense bases</a>, <a href="https://publications.waset.org/abstracts/search?q=Nibb%C4%81na" title=" Nibbāna"> Nibbāna</a> </p> <a href="https://publications.waset.org/abstracts/74800/the-connection-of-the-nibbana-with-the-six-sense-bases" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/74800.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">182</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2479</span> The Patterns of Cross-Sentence: An Event-Related Potential Study of Mathematical Word Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tien-Ching%20Yao">Tien-Ching Yao</a>, <a href="https://publications.waset.org/abstracts/search?q=Ching-Ching%20Lu"> Ching-Ching Lu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Understanding human language processing is one of the main challenges of current cognitive neuroscience. The aims of the present study were to use a sentence decision task combined with event-related potentials to investigate the psychological reality of "cross-sentence patterns." Therefore, we take the math word problems the experimental materials and use the ERPs' P600 component to verify. In this study, the experimental material consisted of 200 math word problems with three different conditions were used ( multiplication word problems、division word problems type 1、division word problems type 2 ). Eighteen Mandarin native speakers participated in the ERPs study (14 of whom were female). The result of the grand average waveforms suggests a later posterior positivity at around 500ms - 900ms. These findings were tested statistically using repeated measures ANOVAs at the component caused by the stimulus type of different questions. Results suggest that three conditions present significant (P < 0.05) on the Mean Amplitude, Latency, and Peak Amplitude. The result showed the characteristic timing and posterior scalp distribution of a P600 effect. We interpreted these characteristic responses as the psychological reality of "cross-sentence patterns." These results provide insights into the sentence processing issues in linguistic theory and psycholinguistic models of language processing and advance our understanding of how people make sense of information during language comprehension. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=language%20processing" title="language processing">language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=sentence%20comprehension" title=" sentence comprehension"> sentence comprehension</a>, <a href="https://publications.waset.org/abstracts/search?q=event-related%20potentials" title=" event-related potentials"> event-related potentials</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-sentence%20patterns" title=" cross-sentence patterns"> cross-sentence patterns</a> </p> <a href="https://publications.waset.org/abstracts/120331/the-patterns-of-cross-sentence-an-event-related-potential-study-of-mathematical-word-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/120331.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">148</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2478</span> Formalizing the Sense Relation of Hyponymy from Logical Point of View: A Study of Mathematical Linguistics in Farsi</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maryam%20Ramezankhani">Maryam Ramezankhani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present research tries to study the possibility of formalizing the sense relation of hyponymy. It applied mathematical tools and also uses mathematical logic concepts especially those from propositional logic. In order to do so, firstly, it goes over the definitions of hyponymy presented in linguistic dictionaries and semantic textbooks. Then, it introduces a formal translation of the sense relation of hyponymy. Lastly, it examines the efficiency of the suggested formula by some examples of natural language. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sense%20relations" title="sense relations">sense relations</a>, <a href="https://publications.waset.org/abstracts/search?q=hyponymy" title=" hyponymy"> hyponymy</a>, <a href="https://publications.waset.org/abstracts/search?q=formalizing" title=" formalizing"> formalizing</a>, <a href="https://publications.waset.org/abstracts/search?q=words%E2%80%99%20sense%20relation" title=" words’ sense relation"> words’ sense relation</a>, <a href="https://publications.waset.org/abstracts/search?q=formalizing%20sense%20relations" title=" formalizing sense relations"> formalizing sense relations</a> </p> <a href="https://publications.waset.org/abstracts/76340/formalizing-the-sense-relation-of-hyponymy-from-logical-point-of-view-a-study-of-mathematical-linguistics-in-farsi" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76340.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">239</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2477</span> Math Word Problems: Context and Achievement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Irena%20Smetackova">Irena Smetackova</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The important part of school mathematics are word problems which represent the connection between school knowledge and life reality. To find the reasons why students consider word problems to be difficult, it is necessary to take into consideration the motivational settings, besides mathematical knowledge and reading skills. Our goal is to identify whether the familiar or unfamiliar context of math word problem influences solving success rate and if so, whether the reasons are motivational or cognitive. For this purpose, we conducted three steps study in group of fifty pupils 9-10 years old. In the first step, we asked pupils to create ‘the best’ word problems for entered numerical formula. The set of 19 word problems with different contexts were selected. In the second step, pupils were asked to evaluate (without solving) how they like each item and how easy it is for them. The 6 word problems with low preference and low estimated success rate were selected and combined with other 6 problems with high preference and success rate. In the third step, the same pupils were asked to solve the word problems. The analysis showed that pupils attitudes and solving toward word problems varied by the context. The strong gender patterns both in preferred contexts and in estimated success rates were identified however the real success rate did not differ so strongly. The success gap between word problems with and without preferred contexts were stronger than the gap between problems with and without real experience with the context. The hypothesis that motivational factors are more important than cognitive factors was confirmed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mathematics" title="mathematics">mathematics</a>, <a href="https://publications.waset.org/abstracts/search?q=context%20of%20reality" title=" context of reality"> context of reality</a>, <a href="https://publications.waset.org/abstracts/search?q=motivation" title=" motivation"> motivation</a>, <a href="https://publications.waset.org/abstracts/search?q=cognition" title=" cognition"> cognition</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20problems" title=" word problems"> word problems</a> </p> <a href="https://publications.waset.org/abstracts/84849/math-word-problems-context-and-achievement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84849.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">198</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2476</span> Network Word Discovery Framework Based on Sentence Semantic Vector Similarity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ganfeng%20Yu">Ganfeng Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Yuefeng%20Ma"> Yuefeng Ma</a>, <a href="https://publications.waset.org/abstracts/search?q=Shanliang%20Yang"> Shanliang Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=text%20information%20retrieval" title="text information retrieval">text information retrieval</a>, <a href="https://publications.waset.org/abstracts/search?q=natural%20language%20processing" title=" natural language processing"> natural language processing</a>, <a href="https://publications.waset.org/abstracts/search?q=new%20word%20discovery" title=" new word discovery"> new word discovery</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20extraction" title=" information extraction"> information extraction</a> </p> <a href="https://publications.waset.org/abstracts/153917/network-word-discovery-framework-based-on-sentence-semantic-vector-similarity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/153917.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">95</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2475</span> The Family Sense of Coherence of Early Childhood Education Students</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Demir">M. Demir</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Demir"> A. Demir</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The aim of this study is to examine the family sense of coherence of early childhood education students. The Family Sense of Coherence Inventory has applied to 233 (108 girls and 125 boys) early childhood education students in Turkey. At the stage of data collection, with the aim of determining the family sense of coherence of early childhood education students, Family Sense of Coherence Inventory which was developed by Çeçen (2007) was used. In the process of the analysis of data, independent samples t-test, and one-way ANOVA were used. According to the results of the study, there were significant differences between some demographic variables in terms of the family sense of coherence. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=family%20sense%20of%20coherence" title="family sense of coherence">family sense of coherence</a>, <a href="https://publications.waset.org/abstracts/search?q=early%20childhood%20education%20students" title=" early childhood education students"> early childhood education students</a> </p> <a href="https://publications.waset.org/abstracts/113400/the-family-sense-of-coherence-of-early-childhood-education-students" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/113400.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">164</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2474</span> Expressivity of Word-Formation in English and Russian Advertising Lexicon</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Voronina%20Ekaterina%20Borisovna">Voronina Ekaterina Borisovna</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The problem of expressivity of advertising lexicon is studied in the article. The comparison of English and Russian advertising lexicons is done. The objects of the analysis were English and Russian advertising texts, both printed advertising texts and texts extracted from the commercials. Some conclusions concerning the expressivity of advertising lexicon were made. Expressivity can be included in the semantic structure of words or created by word-formation means. Expressivity caused by morphological derivatives includes such facilities as derivational affixes, models and types of word formation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=advertising%20lexicon" title="advertising lexicon">advertising lexicon</a>, <a href="https://publications.waset.org/abstracts/search?q=expressivity" title=" expressivity"> expressivity</a>, <a href="https://publications.waset.org/abstracts/search?q=word-formation%20means" title=" word-formation means"> word-formation means</a>, <a href="https://publications.waset.org/abstracts/search?q=linguistics" title=" linguistics"> linguistics</a> </p> <a href="https://publications.waset.org/abstracts/6181/expressivity-of-word-formation-in-english-and-russian-advertising-lexicon" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6181.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">351</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2473</span> Factors Affecting Sense of Community in Residential Communities Case Study: Residential Communities in Tehran, Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Parvin%20Foroughifar">Parvin Foroughifar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The concept of sense of community refers to residents’ sense of attachment and commitment to the other residents in a residential community. It is implicitly indicative of the mental image of a physical environment in which the residents enjoy strong social ties. Sense of community, a crucial factor in improving quality of life and social welfare, leads to life satisfaction in a residential community. Despite the important functions of such a notion, few empirical studies, to the best of the authors' knowledge, have been so far carried out in Iran to investigate the effective factors in sharpening the sense of community in residential communities. This survey research examined sense of community in 360 above 20-year old residents of three residential communities in Tehran, Iran using cluster sampling and questionnaire. The study yielded the result that variables of local social ties, social control and trust, sense of security, length of residence, use of public spaces, and mixed land use have a significant relationship with sense of community. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sense%20of%20community" title="sense of community">sense of community</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20social%20ties" title=" local social ties"> local social ties</a>, <a href="https://publications.waset.org/abstracts/search?q=sense%20of%20security" title=" sense of security"> sense of security</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20space" title=" public space"> public space</a>, <a href="https://publications.waset.org/abstracts/search?q=residential%20community" title=" residential community"> residential community</a>, <a href="https://publications.waset.org/abstracts/search?q=Tehran" title=" Tehran"> Tehran</a> </p> <a href="https://publications.waset.org/abstracts/128887/factors-affecting-sense-of-community-in-residential-communities-case-study-residential-communities-in-tehran-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128887.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">188</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2472</span> Building Semantic-Relatedness Thai Word Ontology for Semantic Analysis</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gridaphat%20Sriharee">Gridaphat Sriharee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Building semantic-relatedness Thai word ontology can be implemented by considering word forms and word meaning. This research proposed the methodology for building the ontology, which can be used for semantic analysis. There are four categories of words: similar form and the same meaning, similar form and similar meaning, different form and opposite/same meaning, and different form and similar meaning, which will be used as initial words for building the proposed ontology. Extension of the ontology can be augmented by considering the messages that give the meaning of the word from the dictionaries. Exploiting WordNet to construct the proposed ontology was investigated and discussed. The proposed ontology was evaluated for its quality. With the proposed methodology, it is promising that the constructed ontology is a well-defined ontology. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Thai" title="Thai">Thai</a>, <a href="https://publications.waset.org/abstracts/search?q=NLP" title=" NLP"> NLP</a>, <a href="https://publications.waset.org/abstracts/search?q=semantics" title=" semantics"> semantics</a>, <a href="https://publications.waset.org/abstracts/search?q=ontology" title=" ontology"> ontology</a> </p> <a href="https://publications.waset.org/abstracts/157354/building-semantic-relatedness-thai-word-ontology-for-semantic-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157354.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">93</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2471</span> Grammatically Coded Corpus of Spoken Lithuanian: Methodology and Development</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=L.%20Kamandulyt%C4%97-Merfeldien%C4%97">L. Kamandulytė-Merfeldienė</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The paper deals with the main issues of methodology of the <em>Corpus of Spoken Lithuanian </em>which was started to be developed in 2006. At present, the corpus consists of 300,000 grammatically annotated word forms. The creation of the corpus consists of three main stages: collecting the data, the transcription of the recorded data, and the grammatical annotation. Collecting the data was based on the principles of balance and naturality. The recorded speech was transcribed according to the CHAT requirements of CHILDES. The transcripts were double-checked and annotated grammatically using CHILDES. The development of the Corpus of Spoken Lithuanian has led to the constant increase in studies on spontaneous communication, and various papers have dealt with a distribution of parts of speech, use of different grammatical forms, variation of inflectional paradigms, distribution of fillers, syntactic functions of adjectives, the mean length of utterances. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=CHILDES" title="CHILDES">CHILDES</a>, <a href="https://publications.waset.org/abstracts/search?q=corpus%20of%20spoken%20Lithuanian" title=" corpus of spoken Lithuanian"> corpus of spoken Lithuanian</a>, <a href="https://publications.waset.org/abstracts/search?q=grammatical%20annotation" title=" grammatical annotation"> grammatical annotation</a>, <a href="https://publications.waset.org/abstracts/search?q=grammatical%20disambiguation" title=" grammatical disambiguation"> grammatical disambiguation</a>, <a href="https://publications.waset.org/abstracts/search?q=lexicon" title=" lexicon"> lexicon</a>, <a href="https://publications.waset.org/abstracts/search?q=Lithuanian" title=" Lithuanian"> Lithuanian</a> </p> <a href="https://publications.waset.org/abstracts/58169/grammatically-coded-corpus-of-spoken-lithuanian-methodology-and-development" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58169.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">236</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2470</span> How Do Undergraduates of Ethnic Minorities Perceive Their Sense of Belonging to School? A Mixed Study in China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiao-Fang%20Wang">Xiao-Fang Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Researchers of educational psychology have proved that students' sense of belonging to school is conducive to their academic achievement, social relations and mental health. However, little attention is paid to undergraduates' sense of belonging, especially, the distinctive student group, i.e., undergraduate students of ethnic minorities. This article utilized a mixed study approach to investigate the perceptions of undergraduates of ethnic minority toward their sense of belonging to school. The findings from qualitative and quantitative data indicate: 1) generally, the sense of belonging to school of ethnic minority undergraduate students was at the middle level. 2) Gender had an important impact on the sense of belonging, and the sense of girls was much larger than boys’. 3) The sense of belonging to school of students who come from city and town was much larger than the one of students who come from the countryside. 4) The category of subjects had significantly effected on the sense of belonging to school, and, the students from social and art science was larger than those from engineer science. The article is concluded with some valuable and relevant suggestions for university' student management activities and teachers' teaching practice. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ethnic%20minority" title="ethnic minority">ethnic minority</a>, <a href="https://publications.waset.org/abstracts/search?q=undergraduate%20students" title=" undergraduate students"> undergraduate students</a>, <a href="https://publications.waset.org/abstracts/search?q=sense%20of%20belonging" title=" sense of belonging"> sense of belonging</a>, <a href="https://publications.waset.org/abstracts/search?q=China" title=" China"> China</a> </p> <a href="https://publications.waset.org/abstracts/35691/how-do-undergraduates-of-ethnic-minorities-perceive-their-sense-of-belonging-to-school-a-mixed-study-in-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/35691.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">449</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2469</span> Pudhaiyal: A Maze-Based Treasure Hunt Game for Tamil Words</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aarthy%20Anandan">Aarthy Anandan</a>, <a href="https://publications.waset.org/abstracts/search?q=Anitha%20Narasimhan"> Anitha Narasimhan</a>, <a href="https://publications.waset.org/abstracts/search?q=Madhan%20Karky"> Madhan Karky</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Word-based games are popular in helping people to improve their vocabulary skills. Games like ‘word search’ and crosswords provide a smart way of increasing vocabulary skills. Word search games are fun to play, but also educational which actually helps to learn a language. Finding the words from word search puzzle helps the player to remember words in an easier way, and it also helps to learn the spellings of words. In this paper, we present a tile distribution algorithm for a Maze-Based Treasure Hunt Game 'Pudhaiyal’ for Tamil words, which describes how words can be distributed horizontally, vertically or diagonally in a 10 x 10 grid. Along with the tile distribution algorithm, we also present an algorithm for the scoring model of the game. The proposed game has been tested with 20,000 Tamil words. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pudhaiyal" title="Pudhaiyal">Pudhaiyal</a>, <a href="https://publications.waset.org/abstracts/search?q=Tamil%20word%20game" title=" Tamil word game"> Tamil word game</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20search" title=" word search"> word search</a>, <a href="https://publications.waset.org/abstracts/search?q=scoring" title=" scoring"> scoring</a>, <a href="https://publications.waset.org/abstracts/search?q=maze" title=" maze"> maze</a>, <a href="https://publications.waset.org/abstracts/search?q=algorithm" title=" algorithm"> algorithm</a> </p> <a href="https://publications.waset.org/abstracts/81334/pudhaiyal-a-maze-based-treasure-hunt-game-for-tamil-words" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/81334.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">440</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2468</span> Number Sense Proficiency and Problem Solving Performance of Grade Seven Students</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Laissa%20Mae%20Francisco">Laissa Mae Francisco</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20Rolex%20Ingreso"> John Rolex Ingreso</a>, <a href="https://publications.waset.org/abstracts/search?q=Anna%20Krizel%20Menguito"> Anna Krizel Menguito</a>, <a href="https://publications.waset.org/abstracts/search?q=Criselda%20Robrigado"> Criselda Robrigado</a>, <a href="https://publications.waset.org/abstracts/search?q=Rej%20Maegan%20%20Tuazon"> Rej Maegan Tuazon</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study aims to determine and describe the existing relationship between number sense proficiency and problem-solving performance of grade seven students from Victorino Mapa High School, Manila. A paper pencil exam containing of 50-item number sense test and 5-item problem-solving test which measures their number sense proficiency and problem-solving performance adapted from McIntosh, Reys, and Bana were used as the research instruments. The data obtained from this study were interpreted and analyzed using the Pearson – Product Moment Coefficient of Correlation to determine the relationship between the two variables. It was found out that students who were low in number sense proficiency tend to be the students with poor problem-solving performance and students with medium number sense proficiency are most likely to have an average problem-solving performance. Likewise, students with high number sense proficiency are those who do excellently in problem-solving performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=number%20sense" title="number sense">number sense</a>, <a href="https://publications.waset.org/abstracts/search?q=performance" title=" performance"> performance</a>, <a href="https://publications.waset.org/abstracts/search?q=problem%20solving" title=" problem solving"> problem solving</a>, <a href="https://publications.waset.org/abstracts/search?q=proficiency" title=" proficiency"> proficiency</a> </p> <a href="https://publications.waset.org/abstracts/59954/number-sense-proficiency-and-problem-solving-performance-of-grade-seven-students" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59954.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">437</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2467</span> The Role of Reading Self-Efficacy and Perception of Difficulty in English Reading among Chinese ESL Learners</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kevin%20Chan">Kevin Chan</a>, <a href="https://publications.waset.org/abstracts/search?q=Kevin%20K.%20H.%20Chung"> Kevin K. H. Chung</a>, <a href="https://publications.waset.org/abstracts/search?q=Patcy%20P.%20S.%20Yeung"> Patcy P. S. Yeung</a>, <a href="https://publications.waset.org/abstracts/search?q=H.%20L.%20Ip"> H. L. Ip</a>, <a href="https://publications.waset.org/abstracts/search?q=Bill%20T.%20C.%20Chung"> Bill T. C. Chung</a>, <a href="https://publications.waset.org/abstracts/search?q=Karen%20M.%20K.%20Chung"> Karen M. K. Chung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Purpose: Recent evidence shows that reading self-efficacy and students perceived difficulty in reading are significantly associated with word reading and reading fluency. However, little is known about these relationships among students learning to read English as a second language, particularly in Chinese students. This study examined the contributions of reading self-efficacy, perception of difficulty in reading, and cognitive-linguistic skills to performance on English word reading and reading fluency in Chinese students. Method: A sample of 122 second-and third-grade students in Hong Kong, China, participated in this study. Students completed the measures of reading self-efficacy and perception of difficulty in reading. They were assessed on their English cognitive-linguistic and reading skills: rapid automatized naming, nonword reading, phonological awareness, word reading, and one-minute word reading. Results: Results of path analysis indicated that when students’ grades were controlled, reading self-efficacy was a significant correlate of word reading and reading fluency, whereas perception of difficulty in reading negatively predicted word reading. Conclusion: These findings underscore the importance of taking students’ reading self-efficacy and perception of difficulty in reading and their cognitive-linguistic skills into consideration when designing reading intervention and instructions for students learning English as a second language. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=self-efficacy" title="self-efficacy">self-efficacy</a>, <a href="https://publications.waset.org/abstracts/search?q=perception%20of%20difficulty%20in%20reading" title=" perception of difficulty in reading"> perception of difficulty in reading</a>, <a href="https://publications.waset.org/abstracts/search?q=english%20as%20a%20second%20language" title=" english as a second language"> english as a second language</a>, <a href="https://publications.waset.org/abstracts/search?q=word%20reading" title=" word reading"> word reading</a> </p> <a href="https://publications.waset.org/abstracts/144471/the-role-of-reading-self-efficacy-and-perception-of-difficulty-in-english-reading-among-chinese-esl-learners" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/144471.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">189</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2466</span> Arabic Light Word Analyser: Roles with Deep Learning Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Abu%20Shquier">Mohammed Abu Shquier</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=NLP" title="NLP">NLP</a>, <a href="https://publications.waset.org/abstracts/search?q=DL" title=" DL"> DL</a>, <a href="https://publications.waset.org/abstracts/search?q=ML" title=" ML"> ML</a>, <a href="https://publications.waset.org/abstracts/search?q=analyser" title=" analyser"> analyser</a>, <a href="https://publications.waset.org/abstracts/search?q=MSA" title=" MSA"> MSA</a>, <a href="https://publications.waset.org/abstracts/search?q=RNN" title=" RNN"> RNN</a>, <a href="https://publications.waset.org/abstracts/search?q=CNN" title=" CNN"> CNN</a> </p> <a href="https://publications.waset.org/abstracts/186026/arabic-light-word-analyser-roles-with-deep-learning-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/186026.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">42</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2465</span> Speech Recognition Performance by Adults: A Proposal for a Battery for Marathi</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20B.%20Rathna%20Kumar">S. B. Rathna Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Pranjali%20A%20Ujwane"> Pranjali A Ujwane</a>, <a href="https://publications.waset.org/abstracts/search?q=Panchanan%20Mohanty"> Panchanan Mohanty</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The present study aimed to develop a battery for assessing speech recognition performance by adults in Marathi. A total of four word lists were developed by considering word frequency, word familiarity, words in common use, and phonemic balance. Each word list consists of 25 words (15 monosyllabic words in CVC structure and 10 monosyllabic words in CVCV structure). Equivalence analysis and performance-intensity function testing was carried using the four word lists on a total of 150 native speakers of Marathi belonging to different regions of Maharashtra (Vidarbha, Marathwada, Khandesh and Northern Maharashtra, Pune, and Konkan). The subjects were further equally divided into five groups based on above mentioned regions. It was found that there was no significant difference (p > 0.05) in the speech recognition performance between groups for each word list and between word lists for each group. Hence, the four word lists developed were equally difficult for all the groups and can be used interchangeably. The performance-intensity (PI) function curve showed semi-linear function, and the groups’ mean slope of the linear portions of the curve indicated an average linear slope of 4.64%, 4.73%, 4.68%, and 4.85% increase in word recognition score per dB for list 1, list 2, list 3 and list 4 respectively. Although, there is no data available on speech recognition tests for adults in Marathi, most of the findings of the study are in line with the findings of research reports on other languages. The four word lists, thus developed, were found to have sufficient reliability and validity in assessing speech recognition performance by adults in Marathi. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=speech%20recognition%20performance" title="speech recognition performance">speech recognition performance</a>, <a href="https://publications.waset.org/abstracts/search?q=phonemic%20balance" title=" phonemic balance"> phonemic balance</a>, <a href="https://publications.waset.org/abstracts/search?q=equivalence%20analysis" title=" equivalence analysis"> equivalence analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=performance-intensity%20function%20testing" title=" performance-intensity function testing"> performance-intensity function testing</a>, <a href="https://publications.waset.org/abstracts/search?q=reliability" title=" reliability"> reliability</a>, <a href="https://publications.waset.org/abstracts/search?q=validity" title=" validity"> validity</a> </p> <a href="https://publications.waset.org/abstracts/41329/speech-recognition-performance-by-adults-a-proposal-for-a-battery-for-marathi" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41329.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">356</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2464</span> Contextual Senses of Ambiguous Words Based on Cognitive Semantics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Madhavi">Madhavi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> All linguistic units are context-dependent. They occur in particular settings, from which they derive much of their import, and are recognized by speakers as distinct entities only through a process of abstraction. Most of the words have several concepts associated with them and convey a number of meanings in different contexts in any language. For instance, there are different uses of the word good as an adjective from English. The adjective good expresses many senses like (1) ‘high quality of someone or something’ (2) ‘efficient’ (3) ‘virtuous’ (4) ‘reliable’ etc. These senses will be analyzed by using cognitive semantics framework. The context has the power to insulate one meaning from all the other meanings in communication. This paper will provide a cognitive semantic analysis. The basic tenet of cognitive semantics is the sense of a word is the way we conceptualize it. Our conceptualization is based on the physical experience we go through. Cognitive semantics tries to capture this conceptualization in terms of some categories like schema, frame, and domain. Cognitive semantics is a subfield of cognitive linguistics. Cognitive linguistics studies the language creation, learning, and usage by the reference to human cognition. The semantic structure is conceptual structure which is related to the concepts which are the elements of reason and constitute the meanings of words and linguistic expressions. Cognitive semantics studies how our mind works for the meaning of any word and how it perceives meaning from the environment through senses and works to map with the knowledge which already exists in our mind through experience. In the present paper, the senses are further classified into some categories. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive" title="cognitive">cognitive</a>, <a href="https://publications.waset.org/abstracts/search?q=contexts" title=" contexts"> contexts</a>, <a href="https://publications.waset.org/abstracts/search?q=semantics" title=" semantics"> semantics</a>, <a href="https://publications.waset.org/abstracts/search?q=senses" title=" senses"> senses</a> </p> <a href="https://publications.waset.org/abstracts/79391/contextual-senses-of-ambiguous-words-based-on-cognitive-semantics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/79391.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">219</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2463</span> Sentence Structure for Free Word Order Languages in Context with Anaphora Resolution: A Case Study of Hindi </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pardeep%20Singh">Pardeep Singh</a>, <a href="https://publications.waset.org/abstracts/search?q=Kamlesh%20Dutta"> Kamlesh Dutta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Many languages have fixed sentence structure and others are free word order. The accuracy of anaphora resolution of syntax based algorithm depends on structure of the sentence. So, it is important to analyze the structure of any language before implementing these algorithms. In this study, we analyzed the sentence structure exploiting the case marker in Hindi as well as some special tag for subject and object. We also investigated the word order for Hindi. Word order typology refers to the study of the order of the syntactic constituents of a language. We analyzed 165 news items of Ranchi Express from EMILEE corpus of plain text. It consisted of 1745 sentences. Eight file of dialogue based from the same corpus has been analyzed which will have 1521 sentences. The percentages of subject object verb structure (SOV) and object subject verb (OSV) are 66.90 and 33.10, respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=anaphora%20resolution" title="anaphora resolution">anaphora resolution</a>, <a href="https://publications.waset.org/abstracts/search?q=free%20word%20order%20languages" title=" free word order languages"> free word order languages</a>, <a href="https://publications.waset.org/abstracts/search?q=SOV" title=" SOV"> SOV</a>, <a href="https://publications.waset.org/abstracts/search?q=OSV" title=" OSV"> OSV</a> </p> <a href="https://publications.waset.org/abstracts/9937/sentence-structure-for-free-word-order-languages-in-context-with-anaphora-resolution-a-case-study-of-hindi" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9937.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">472</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2462</span> Effects of Word Formation Dissimilarities on Youruba Learners of English</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pelumi%20Olowofoyeku">Pelumi Olowofoyeku</a> </p> <p class="card-text"><strong>Abstract:</strong></p> English as a language has great reach and influence; it is taught all over the world. For instance, in Nigeria, English language is been taught and learned as a second language; therefore second learners of English in Nigeria have certain problems they contend with. Because of the dissimilarities in word formation patterns of English and Yoruba languages, Yoruba learners of English mostly found in the south west of Nigeria, and some parts of Kwara, Kogi, and Edo states of Nigeria have problems with word formation patterns in English. The objectives of this paper therefore, are: to identify the levels of word formation dissimilarities in English and Yoruba languages and to examine the effects of these dissimilarities on the Yoruba learners of English. The data for this paper were graded words purposely selected and presented to selected students of Adeniran Ogunsanya College of Education, Oto-Ijanikin, Lagos, who are Yoruba learners of English. These respondents were randomly selected to form words which are purposively selected to test the effects of word formation dissimilarities between Yoruba (the respondent’s first language) and English language on the respondents. The dissimilarities are examined using contrastive analysis tools. This paper reveals that there are differences in the word formation patterns of Yoruba and English languages. The writer believes that there is need for language teachers to undertake comparative studies of the two languages involved for methodological reasons. The author then suggests that teachers should identify the problem areas and systematically teach their students. The paper concludes that although English and Yoruba word formation patterns differ very significantly in many respects, there exist language universals in all languages which language educators should take advantage of in teaching. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=word%20formation%20patterns" title="word formation patterns">word formation patterns</a>, <a href="https://publications.waset.org/abstracts/search?q=graded%20words" title=" graded words"> graded words</a>, <a href="https://publications.waset.org/abstracts/search?q=ESL" title=" ESL"> ESL</a>, <a href="https://publications.waset.org/abstracts/search?q=Yoruba%20learners" title=" Yoruba learners"> Yoruba learners</a> </p> <a href="https://publications.waset.org/abstracts/34953/effects-of-word-formation-dissimilarities-on-youruba-learners-of-english" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/34953.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">499</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=word%20sense%20disambiguation&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=word%20sense%20disambiguation&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=word%20sense%20disambiguation&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=word%20sense%20disambiguation&page=5">5</a></li> <li class="page-item"><a class="page-link" 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