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technique</title> <meta name="description" content="Search results for: mining technique"> <meta name="keywords" content="mining technique"> <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 class="d-block d-lg-none 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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="mining technique"> <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> 7534</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: mining technique</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7534</span> A Comprehensive Survey and Improvement to Existing Privacy Preserving Data Mining Techniques</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tosin%20Ige">Tosin Ige</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data" title="data">data</a>, <a href="https://publications.waset.org/abstracts/search?q=privacy" title=" privacy"> privacy</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=association%20rule" title=" association rule"> association rule</a>, <a href="https://publications.waset.org/abstracts/search?q=privacy%20preserving" title=" privacy preserving"> privacy preserving</a>, <a href="https://publications.waset.org/abstracts/search?q=mining%20technique" title=" mining technique"> mining technique</a> </p> <a href="https://publications.waset.org/abstracts/145870/a-comprehensive-survey-and-improvement-to-existing-privacy-preserving-data-mining-techniques" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/145870.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">173</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">7533</span> Knowledge Discovery and Data Mining Techniques in Textile Industry</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Filiz%20Ersoz">Filiz Ersoz</a>, <a href="https://publications.waset.org/abstracts/search?q=Taner%20Ersoz"> Taner Ersoz</a>, <a href="https://publications.waset.org/abstracts/search?q=Erkin%20Guler"> Erkin Guler</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title="data mining">data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=textile%20production" title=" textile production"> textile production</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20trees" title=" decision trees"> decision trees</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/75461/knowledge-discovery-and-data-mining-techniques-in-textile-industry" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75461.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">349</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">7532</span> Harmonic Data Preparation for Clustering and Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Asheibi">Ali Asheibi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The rapid increase in the size of databases required to store power quality monitoring data has demanded new techniques for analysing and understanding the data. One suggested technique to assist in analysis is data mining. Preparing raw data to be ready for data mining exploration take up most of the effort and time spent in the whole data mining process. Clustering is an important technique in data mining and machine learning in which underlying and meaningful groups of data are discovered. Large amounts of harmonic data have been collected from an actual harmonic monitoring system in a distribution system in Australia for three years. This amount of acquired data makes it difficult to identify operational events that significantly impact the harmonics generated on the system. In this paper, harmonic data preparation processes to better understanding of the data have been presented. Underlying classes in this data has then been identified using clustering technique based on the Minimum Message Length (MML) method. The underlying operational information contained within the clusters can be rapidly visualised by the engineers. The C5.0 algorithm was used for classification and interpretation of the generated clusters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title="data mining">data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=harmonic%20data" title=" harmonic data"> harmonic data</a>, <a href="https://publications.waset.org/abstracts/search?q=clustering" title=" clustering"> clustering</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a> </p> <a href="https://publications.waset.org/abstracts/80801/harmonic-data-preparation-for-clustering-and-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80801.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">248</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">7531</span> Analysis of Users’ Behavior on Book Loan Log Based on Association Rule Mining </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kanyarat%20Bussaban">Kanyarat Bussaban</a>, <a href="https://publications.waset.org/abstracts/search?q=Kunyanuth%20Kularbphettong"> Kunyanuth Kularbphettong </a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=behavior" title="behavior">behavior</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining%20technique" title=" data mining technique"> data mining technique</a>, <a href="https://publications.waset.org/abstracts/search?q=a%20priori%20algorithm" title=" a priori algorithm"> a priori algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20discovery" title=" knowledge discovery"> knowledge discovery</a> </p> <a href="https://publications.waset.org/abstracts/2673/analysis-of-users-behavior-on-book-loan-log-based-on-association-rule-mining" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2673.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">404</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">7530</span> Review of Different Machine Learning Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Syed%20Romat%20Ali%20Shah">Syed Romat Ali Shah</a>, <a href="https://publications.waset.org/abstracts/search?q=Bilal%20Shoaib"> Bilal Shoaib</a>, <a href="https://publications.waset.org/abstracts/search?q=Saleem%20Akhtar"> Saleem Akhtar</a>, <a href="https://publications.waset.org/abstracts/search?q=Munib%20Ahmad"> Munib Ahmad</a>, <a href="https://publications.waset.org/abstracts/search?q=Shahan%20Sadiqui"> Shahan Sadiqui</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Data%20Mining" title="Data Mining">Data Mining</a>, <a href="https://publications.waset.org/abstracts/search?q=Web%20Mining" title=" Web Mining"> Web Mining</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=ML%20Algorithms" title=" ML Algorithms"> ML Algorithms</a> </p> <a href="https://publications.waset.org/abstracts/124105/review-of-different-machine-learning-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/124105.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">303</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">7529</span> A Review Paper on Data Mining and Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sikander%20Singh%20Cheema">Sikander Singh Cheema</a>, <a href="https://publications.waset.org/abstracts/search?q=Jasmeen%20Kaur"> Jasmeen Kaur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, the concept of data mining is summarized and its one of the important process i.e KDD is summarized. The data mining based on Genetic Algorithm is researched in and ways to achieve the data mining Genetic Algorithm are surveyed. This paper also conducts a formal review on the area of data mining tasks and genetic algorithm in various fields. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title="data mining">data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=KDD" title=" KDD"> KDD</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=descriptive%20mining" title=" descriptive mining"> descriptive mining</a>, <a href="https://publications.waset.org/abstracts/search?q=predictive%20mining" title=" predictive mining"> predictive mining</a> </p> <a href="https://publications.waset.org/abstracts/43637/a-review-paper-on-data-mining-and-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43637.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">591</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">7528</span> Analysis of Different Classification Techniques Using WEKA for Diabetic Disease </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Usama%20Ahmed">Usama Ahmed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title="data mining">data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=diabetes" title=" diabetes"> diabetes</a>, <a href="https://publications.waset.org/abstracts/search?q=WEKA" title=" WEKA"> WEKA</a> </p> <a href="https://publications.waset.org/abstracts/127192/analysis-of-different-classification-techniques-using-weka-for-diabetic-disease" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127192.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">147</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">7527</span> Privacy Preserving in Association Rule Mining on Horizontally Partitioned Database</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Manvar%20Sagar">Manvar Sagar</a>, <a href="https://publications.waset.org/abstracts/search?q=Nikul%20Virpariya"> Nikul Virpariya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The advancement in data mining techniques plays an important role in many applications. In context of privacy and security issues, the problems caused by association rule mining technique are investigated by many research scholars. It is proved that the misuse of this technique may reveal the database owner’s sensitive and private information to others. Many researchers have put their effort to preserve privacy in Association Rule Mining. Amongst the two basic approaches for privacy preserving data mining, viz. Randomization based and Cryptography based, the later provides high level of privacy but incurs higher computational as well as communication overhead. Hence, it is necessary to explore alternative techniques that improve the over-heads. In this work, we propose an efficient, collusion-resistant cryptography based approach for distributed Association Rule mining using Shamir’s secret sharing scheme. As we show from theoretical and practical analysis, our approach is provably secure and require only one time a trusted third party. We use secret sharing for privately sharing the information and code based identification scheme to add support against malicious adversaries. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Privacy" title="Privacy">Privacy</a>, <a href="https://publications.waset.org/abstracts/search?q=Privacy%20Preservation%20in%20Data%20Mining%20%28PPDM%29" title=" Privacy Preservation in Data Mining (PPDM)"> Privacy Preservation in Data Mining (PPDM)</a>, <a href="https://publications.waset.org/abstracts/search?q=horizontally%20partitioned%20database" title=" horizontally partitioned database"> horizontally partitioned database</a>, <a href="https://publications.waset.org/abstracts/search?q=EMHS" title=" EMHS"> EMHS</a>, <a href="https://publications.waset.org/abstracts/search?q=MFI" title=" MFI"> MFI</a>, <a href="https://publications.waset.org/abstracts/search?q=shamir%20secret%20sharing" title=" shamir secret sharing"> shamir secret sharing</a> </p> <a href="https://publications.waset.org/abstracts/20983/privacy-preserving-in-association-rule-mining-on-horizontally-partitioned-database" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20983.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">408</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">7526</span> Mining Big Data in Telecommunications Industry: Challenges, Techniques, and Revenue Opportunity</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hoda%20A.%20Abdel%20Hafez">Hoda A. Abdel Hafez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mining%20big%20data" title="mining big data">mining big data</a>, <a href="https://publications.waset.org/abstracts/search?q=big%20data" title=" big data"> big data</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=telecommunication" title=" telecommunication"> telecommunication</a> </p> <a href="https://publications.waset.org/abstracts/41412/mining-big-data-in-telecommunications-industry-challenges-techniques-and-revenue-opportunity" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/41412.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">410</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">7525</span> Mining Educational Data to Support Students’ Major Selection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kunyanuth%20Kularbphettong">Kunyanuth Kularbphettong</a>, <a href="https://publications.waset.org/abstracts/search?q=Cholticha%20Tongsiri"> Cholticha Tongsiri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20mining%20technique" title="data mining technique">data mining technique</a>, <a href="https://publications.waset.org/abstracts/search?q=the%20decision%20support%20system" title=" the decision support system"> the decision support system</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20and%20decision%20rules" title=" knowledge and decision rules"> knowledge and decision rules</a>, <a href="https://publications.waset.org/abstracts/search?q=education" title=" education"> education</a> </p> <a href="https://publications.waset.org/abstracts/2788/mining-educational-data-to-support-students-major-selection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2788.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">423</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">7524</span> Data Mining As A Tool For Knowledge Management: A Review </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maram%20Saleh">Maram Saleh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Data%20Mining" title="Data Mining">Data Mining</a>, <a href="https://publications.waset.org/abstracts/search?q=Knowledge%20management" title=" Knowledge management"> Knowledge management</a>, <a href="https://publications.waset.org/abstracts/search?q=Knowledge%20discovery" title=" Knowledge discovery"> Knowledge discovery</a>, <a href="https://publications.waset.org/abstracts/search?q=Knowledge%20creation." title=" Knowledge creation."> Knowledge creation.</a> </p> <a href="https://publications.waset.org/abstracts/137030/data-mining-as-a-tool-for-knowledge-management-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/137030.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">208</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">7523</span> A Data Mining Approach for Analysing and Predicting the Bank's Asset Liability Management Based on Basel III Norms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nidhin%20Dani%20Abraham">Nidhin Dani Abraham</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20K.%20Sri%20Shilpa"> T. K. Sri Shilpa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Asset liability management is an important aspect in banking business. Moreover, the today’s banking is based on BASEL III which strictly regulates on the counterparty default. This paper focuses on prediction and analysis of counter party default risk, which is a type of risk occurs when the customers fail to repay the amount back to the lender (bank or any financial institutions). This paper proposes an approach to reduce the counterparty risk occurring in the financial institutions using an appropriate data mining technique and thus predicts the occurrence of NPA. It also helps in asset building and restructuring quality. Liability management is very important to carry out banking business. To know and analyze the depth of liability of bank, a suitable technique is required. For that a data mining technique is being used to predict the dormant behaviour of various deposit bank customers. Various models are implemented and the results are analyzed of saving bank deposit customers. All these data are cleaned using data cleansing approach from the bank data warehouse. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title="data mining">data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=asset%20liability%20management" title=" asset liability management"> asset liability management</a>, <a href="https://publications.waset.org/abstracts/search?q=BASEL%20III" title=" BASEL III"> BASEL III</a>, <a href="https://publications.waset.org/abstracts/search?q=banking" title=" banking"> banking</a> </p> <a href="https://publications.waset.org/abstracts/9884/a-data-mining-approach-for-analysing-and-predicting-the-banks-asset-liability-management-based-on-basel-iii-norms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9884.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">552</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">7522</span> Project Risk Assessment of the Mining Industry of Ghana</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Charles%20Amoatey">Charles Amoatey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The issue of risk in the mining industry is a global phenomenon and the Ghanaian mining industry is not exempted. The main purpose of this study is to identify the critical risk factors affecting the mining industry. The study takes an integrated view of the mining industry by examining the contribution of various risk factors to mining project failure in Ghana. A questionnaire survey was conducted to solicit the critical risk factors from key mining practitioners. About 80 respondents from 11 mining firms participated in the survey. The study identified 22 risk factors contributing to mining project failure in Ghana. The five most critical risk factors based on both probability of occurrence and impact were: (1) unstable commodity prices, (2) inflation/exchange rate, (3) land degradation, (4) high cost of living and (5) government bureaucracy for obtaining licenses. Furthermore, the study found that risk assessment in the mining sector has a direct link with mining project sustainability. Mitigation measures for addressing the identified risk factors were discussed. The key findings emphasize the need for a comprehensive risk management culture in the entire mining industry. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=risk" title="risk">risk</a>, <a href="https://publications.waset.org/abstracts/search?q=assessment" title=" assessment"> assessment</a>, <a href="https://publications.waset.org/abstracts/search?q=mining" title=" mining"> mining</a>, <a href="https://publications.waset.org/abstracts/search?q=Ghana" title=" Ghana"> Ghana</a> </p> <a href="https://publications.waset.org/abstracts/48909/project-risk-assessment-of-the-mining-industry-of-ghana" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48909.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">452</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">7521</span> Assessment for the Backfill Using the Run of the Mine Tailings and Portland Cement </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Javad%20Someehneshin">Javad Someehneshin</a>, <a href="https://publications.waset.org/abstracts/search?q=Weizhou%20Quan"> Weizhou Quan</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdelsalam%20Abugharara"> Abdelsalam Abugharara</a>, <a href="https://publications.waset.org/abstracts/search?q=Stephen%20Butt"> Stephen Butt</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Narrow vein mining (NVM) is exploiting very thin but valuable ore bodies that are uneconomical to extract by conventional mining methods. NVM applies the technique of Sustainable Mining by Drilling (SMD). The SMD method is used to mine stranded, steeply dipping ore veins, which are too small or isolated to mine economically using conventional methods since the dilution is minimized. This novel mining technique uses drilling rigs to extract the ore through directional drilling surgically. This paper is focusing on utilizing the run of the mine tailings and Portland cement as backfill material to support the hanging wall for providing safe mine operation. Cemented paste backfill (CPB) is designed by mixing waste tailings, water, and cement of the precise percentage for optimal outcomes. It is a non-homogenous material that contains 70-85% solids. Usually, a hydraulic binder is added to the mixture to increase the strength of the CPB. The binder fraction mostly accounts for 2–10% of the total weight. In the mining industry, CPB has been improved and expanded gradually because it provides safety and support for the mines. Furthermore, CPB helps manage the waste tailings in an economical method and plays a significant role in environmental protection. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=backfilling" title="backfilling">backfilling</a>, <a href="https://publications.waset.org/abstracts/search?q=cement%20backfill" title=" cement backfill"> cement backfill</a>, <a href="https://publications.waset.org/abstracts/search?q=tailings" title=" tailings"> tailings</a>, <a href="https://publications.waset.org/abstracts/search?q=Portland%20cement" title=" Portland cement"> Portland cement</a> </p> <a href="https://publications.waset.org/abstracts/125089/assessment-for-the-backfill-using-the-run-of-the-mine-tailings-and-portland-cement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/125089.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">138</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">7520</span> Forecasting Unusual Infection of Patient Used by Irregular Weighted Point Set</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seema%20Vaidya">Seema Vaidya</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Mining association rule is a key issue in data mining. In any case, the standard models ignore the distinction among the exchanges, and the weighted association rule mining does not transform on databases with just binary attributes. This paper proposes a novel continuous example and executes a tree (FP-tree) structure, which is an increased prefix-tree structure for securing compacted, discriminating data about examples, and makes a fit FP-tree-based mining system, FP enhanced capacity algorithm is used, for mining the complete game plan of examples by illustration incessant development. Here, this paper handles the motivation behind making remarkable and weighted item sets, i.e. rare weighted item set mining issue. The two novel brightness measures are proposed for figuring the infrequent weighted item set mining issue. Also, the algorithm are handled which perform IWI which is more insignificant IWI mining. Moreover we utilized the rare item set for choice based structure. The general issue of the start of reliable definite rules is troublesome for the grounds that hypothetically no inciting technique with no other person can promise the rightness of influenced theories. In this way, this framework expects the disorder with the uncommon signs. Usage study demonstrates that proposed algorithm upgrades the structure which is successful and versatile for mining both long and short diagnostics rules. Structure upgrades aftereffects of foreseeing rare diseases of patient. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=association%20rule" title="association rule">association rule</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=IWI%20mining" title=" IWI mining"> IWI mining</a>, <a href="https://publications.waset.org/abstracts/search?q=infrequent%20item%20set" title=" infrequent item set"> infrequent item set</a>, <a href="https://publications.waset.org/abstracts/search?q=frequent%20pattern%20growth" title=" frequent pattern growth"> frequent pattern growth</a> </p> <a href="https://publications.waset.org/abstracts/32862/forecasting-unusual-infection-of-patient-used-by-irregular-weighted-point-set" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32862.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">399</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">7519</span> Application of Remote Sensing Technique on the Monitoring of Mine Eco-Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Haidong%20Li">Haidong Li</a>, <a href="https://publications.waset.org/abstracts/search?q=Weishou%20Shen"> Weishou Shen</a>, <a href="https://publications.waset.org/abstracts/search?q=Guoping%20Lv"> Guoping Lv</a>, <a href="https://publications.waset.org/abstracts/search?q=Tao%20Wang"> Tao Wang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=LiDAR" title="LiDAR">LiDAR</a>, <a href="https://publications.waset.org/abstracts/search?q=mine" title=" mine"> mine</a>, <a href="https://publications.waset.org/abstracts/search?q=ecological%20damage" title=" ecological damage"> ecological damage</a>, <a href="https://publications.waset.org/abstracts/search?q=monitoring" title=" monitoring"> monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=traditional%20remote%20sensing%20technique" title=" traditional remote sensing technique"> traditional remote sensing technique</a> </p> <a href="https://publications.waset.org/abstracts/65821/application-of-remote-sensing-technique-on-the-monitoring-of-mine-eco-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65821.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">397</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">7518</span> A Review on Existing Challenges of Data Mining and Future Research Perspectives</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hema%20Bhardwaj">Hema Bhardwaj</a>, <a href="https://publications.waset.org/abstracts/search?q=D.%20Srinivasa%20Rao"> D. Srinivasa Rao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=big%20data" title="big data">big data</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20analysis" title=" data analysis"> data analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20discovery%20techniques" title=" knowledge discovery techniques"> knowledge discovery techniques</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining%20challenges" title=" data mining challenges"> data mining challenges</a> </p> <a href="https://publications.waset.org/abstracts/160836/a-review-on-existing-challenges-of-data-mining-and-future-research-perspectives" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160836.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">110</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">7517</span> Application of Artificial Neural Network Technique for Diagnosing Asthma</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Azadeh%20Bashiri">Azadeh Bashiri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=asthma" title="asthma">asthma</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=Artificial%20Neural%20Network" title=" Artificial Neural Network"> Artificial Neural Network</a>, <a href="https://publications.waset.org/abstracts/search?q=intelligent%20system" title=" intelligent system"> intelligent system</a> </p> <a href="https://publications.waset.org/abstracts/43554/application-of-artificial-neural-network-technique-for-diagnosing-asthma" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43554.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">273</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">7516</span> Block Mining: Block Chain Enabled Process Mining Database</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=James%20Newman">James Newman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=blockchain" title="blockchain">blockchain</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20mining" title=" process mining"> process mining</a>, <a href="https://publications.waset.org/abstracts/search?q=memory%20optimization" title=" memory optimization"> memory optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=protocol" title=" protocol"> protocol</a> </p> <a href="https://publications.waset.org/abstracts/166846/block-mining-block-chain-enabled-process-mining-database" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/166846.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">102</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">7515</span> Association Rules Mining Task Using Metaheuristics: Review</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abir%20Derouiche">Abir Derouiche</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdesslem%20Layeb"> Abdesslem Layeb </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Association Rule Mining (ARM) is one of the most popular data mining tasks and it is widely used in various areas. The search for association rules is an NP-complete problem that is why metaheuristics have been widely used to solve it. The present paper presents the ARM as an optimization problem and surveys the proposed approaches in the literature based on metaheuristics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Optimization" title="Optimization">Optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=Metaheuristics" title=" Metaheuristics"> Metaheuristics</a>, <a href="https://publications.waset.org/abstracts/search?q=Data%20Mining" title=" Data Mining"> Data Mining</a>, <a href="https://publications.waset.org/abstracts/search?q=Association%20rules%20Mining" title=" Association rules Mining"> Association rules Mining</a> </p> <a href="https://publications.waset.org/abstracts/120254/association-rules-mining-task-using-metaheuristics-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/120254.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">159</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">7514</span> Study for Establishing a Concept of Underground Mining in a Folded Deposit with Weathering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chandan%20Pramanik">Chandan Pramanik</a>, <a href="https://publications.waset.org/abstracts/search?q=Bikramjit%20Chanda"> Bikramjit Chanda</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Large metal mines operated with open-cast mining methods must transition to underground mining at the conclusion of the operation; however, this requires a period of a difficult time when production convergence due to interference between the two mining methods. A transition model with collaborative mining operations is presented and established in this work, based on the case of the South Kaliapani Underground Project, to address these technical issues of inadequate production security and other mining challenges during the transition phase and beyond. By integrating the technology of the small-scale Drift and Fill method and Highly productive Sub Level Open Stoping at deep section, this hybrid mining concept tries to eliminate major bottlenecks and offers an optimized production profile with the safe and sustainable operation. Considering every geo-mining aspect, this study offers a genuine and precise technical deliberation for the transition from open pit to underground mining. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=drift%20and%20fill" title="drift and fill">drift and fill</a>, <a href="https://publications.waset.org/abstracts/search?q=geo-mining%20aspect" title=" geo-mining aspect"> geo-mining aspect</a>, <a href="https://publications.waset.org/abstracts/search?q=sublevel%20open%20stoping" title=" sublevel open stoping"> sublevel open stoping</a>, <a href="https://publications.waset.org/abstracts/search?q=underground%20mining%20method" title=" underground mining method"> underground mining method</a> </p> <a href="https://publications.waset.org/abstracts/160119/study-for-establishing-a-concept-of-underground-mining-in-a-folded-deposit-with-weathering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160119.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">100</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">7513</span> The Environmental and Socio Economic Impacts of Mining on Local Livelihood in Cameroon: A Case Study in Bertoua</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fongang%20Robert%20Tichuck">Fongang Robert Tichuck</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper reports the findings of a study undertaken to assess the socio-economic and environmental impacts of mining in Bertoua Eastern Region of Cameroon. In addition to sampling community perceptions of mining activities, the study prescribes interventions that can assist in mitigating the negative impacts of mining. Marked environmental and interrelated socio-economic improvements can be achieved within regional artisanal gold mines if the government provides technical support to local operators, regulations are improved, and illegal mining activity is reduced. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=gold%20mining" title="gold mining">gold mining</a>, <a href="https://publications.waset.org/abstracts/search?q=socio-economic" title=" socio-economic"> socio-economic</a>, <a href="https://publications.waset.org/abstracts/search?q=mining%20activities" title=" mining activities"> mining activities</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20people" title=" local people"> local people</a> </p> <a href="https://publications.waset.org/abstracts/42339/the-environmental-and-socio-economic-impacts-of-mining-on-local-livelihood-in-cameroon-a-case-study-in-bertoua" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42339.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">396</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">7512</span> Analyzing Tools and Techniques for Classification In Educational Data Mining: A Survey</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=D.%20I.%20George%20Amalarethinam">D. I. George Amalarethinam</a>, <a href="https://publications.waset.org/abstracts/search?q=A.%20Emima"> A. Emima</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Educational Data Mining (EDM) is one of the newest topics to emerge in recent years, and it is concerned with developing methods for analyzing various types of data gathered from the educational circle. EDM methods and techniques with machine learning algorithms are used to extract meaningful and usable information from huge databases. For scientists and researchers, realistic applications of Machine Learning in the EDM sectors offer new frontiers and present new problems. One of the most important research areas in EDM is predicting student success. The prediction algorithms and techniques must be developed to forecast students' performance, which aids the tutor, institution to boost the level of student’s performance. This paper examines various classification techniques in prediction methods and data mining tools used in EDM. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification%20technique" title="classification technique">classification technique</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=EDM%20methods" title=" EDM methods"> EDM methods</a>, <a href="https://publications.waset.org/abstracts/search?q=prediction%20methods" title=" prediction methods"> prediction methods</a> </p> <a href="https://publications.waset.org/abstracts/146484/analyzing-tools-and-techniques-for-classification-in-educational-data-mining-a-survey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146484.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">117</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">7511</span> Spontaneous Message Detection of Annoying Situation in Community Networks Using Mining Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=P.%20Senthil%20Kumari">P. Senthil Kumari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=text%20mining" title="text mining">text mining</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20classification" title=" data classification"> data classification</a>, <a href="https://publications.waset.org/abstracts/search?q=community%20network" title=" community network"> community network</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20algorithm" title=" learning algorithm"> learning algorithm</a> </p> <a href="https://publications.waset.org/abstracts/27184/spontaneous-message-detection-of-annoying-situation-in-community-networks-using-mining-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/27184.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">508</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">7510</span> Frequent Item Set Mining for Big Data Using MapReduce Framework</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tamanna%20Jethava">Tamanna Jethava</a>, <a href="https://publications.waset.org/abstracts/search?q=Rahul%20Joshi"> Rahul Joshi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=frequent%20item%20set%20mining" title="frequent item set mining">frequent item set mining</a>, <a href="https://publications.waset.org/abstracts/search?q=big%20data" title=" big data"> big data</a>, <a href="https://publications.waset.org/abstracts/search?q=Hadoop" title=" Hadoop"> Hadoop</a>, <a href="https://publications.waset.org/abstracts/search?q=MapReduce" title=" MapReduce"> MapReduce</a> </p> <a href="https://publications.waset.org/abstracts/49592/frequent-item-set-mining-for-big-data-using-mapreduce-framework" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49592.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">436</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">7509</span> Using Data Mining Technique for Scholarship Disbursement</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=J.%20K.%20Alhassan">J. K. Alhassan</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20A.%20Lawal"> S. A. Lawal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work is on decision tree-based classification for the disbursement of scholarship. Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. The system based on the defined rules from the tree is able to determine the class (status) to which an applicant shall belong whether Granted or Not Granted. The applicants that fall to the class of granted denote a successful acquirement of scholarship while those in not granted class are unsuccessful in the scheme. An algorithm that can be used to classify the applicants based on the rules from tree-based classification was also developed. The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. The system was tested with the data of National Information Technology Development Agency (NITDA) Abuja, a Parastatal of Federal Ministry of Communication Technology that is mandated to develop and regulate information technology in Nigeria. The system was found working according to the specification. It is therefore recommended for all scholarship disbursement organizations. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=classification" title="classification">classification</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=decision%20tree" title=" decision tree"> decision tree</a>, <a href="https://publications.waset.org/abstracts/search?q=scholarship" title=" scholarship"> scholarship</a> </p> <a href="https://publications.waset.org/abstracts/30987/using-data-mining-technique-for-scholarship-disbursement" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30987.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">376</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">7508</span> Business-Intelligence Mining of Large Decentralized Multimedia Datasets with a Distributed Multi-Agent System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Karima%20Qayumi">Karima Qayumi</a>, <a href="https://publications.waset.org/abstracts/search?q=Alex%20Norta"> Alex Norta</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The rapid generation of high volume and a broad variety of data from the application of new technologies pose challenges for the generation of business-intelligence. Most organizations and business owners need to extract data from multiple sources and apply analytical methods for the purposes of developing their business. Therefore, the recently decentralized data management environment is relying on a distributed computing paradigm. While data are stored in highly distributed systems, the implementation of distributed data-mining techniques is a challenge. The aim of this technique is to gather knowledge from every domain and all the datasets stemming from distributed resources. As agent technologies offer significant contributions for managing the complexity of distributed systems, we consider this for next-generation data-mining processes. To demonstrate agent-based business intelligence operations, we use agent-oriented modeling techniques to develop a new artifact for mining massive datasets. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=agent-oriented%20modeling%20%28AOM%29" title="agent-oriented modeling (AOM)">agent-oriented modeling (AOM)</a>, <a href="https://publications.waset.org/abstracts/search?q=business%20intelligence%20model%20%28BIM%29" title=" business intelligence model (BIM)"> business intelligence model (BIM)</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20data%20mining%20%28DDM%29" title=" distributed data mining (DDM)"> distributed data mining (DDM)</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-agent%20system%20%28MAS%29" title=" multi-agent system (MAS)"> multi-agent system (MAS)</a> </p> <a href="https://publications.waset.org/abstracts/44164/business-intelligence-mining-of-large-decentralized-multimedia-datasets-with-a-distributed-multi-agent-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/44164.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">432</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">7507</span> Medical Knowledge Management since the Integration of Heterogeneous Data until the Knowledge Exploitation in a Decision-Making System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nadjat%20Zerf%20Boudjettou">Nadjat Zerf Boudjettou</a>, <a href="https://publications.waset.org/abstracts/search?q=Fahima%20Nader"> Fahima Nader</a>, <a href="https://publications.waset.org/abstracts/search?q=Rachid%20Chalal"> Rachid Chalal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=data%20warehouse" title="data warehouse">data warehouse</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge%20discovery%20in%20database" title=" knowledge discovery in database"> knowledge discovery in database</a>, <a href="https://publications.waset.org/abstracts/search?q=KDD" title=" KDD"> KDD</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20knowledge%20management" title=" medical knowledge management"> medical knowledge management</a>, <a href="https://publications.waset.org/abstracts/search?q=Bayesian%20networks" title=" Bayesian networks"> Bayesian networks</a> </p> <a href="https://publications.waset.org/abstracts/14543/medical-knowledge-management-since-the-integration-of-heterogeneous-data-until-the-knowledge-exploitation-in-a-decision-making-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14543.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">395</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">7506</span> Identification of Environmental Damage Due to Mining Area Bangka Islands in Indonesia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aroma%20Elmina%20Martha">Aroma Elmina Martha</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Environment affects the continuity of life and human well-being and the bodies of other living. Environmental quality is very closely related to the quality of life. Sustainability must be protected from damage due to the use of natural resources, such as tin mining in Bangka island. This research is a descriptive study, which identifies the environmental damage caused by mining land and sea in Bangka district. The approach used is juridical, social and economic. The study uses primary legal materials, secondary, and tertiary, equipped with field research. The analysis technique used is qualitative analysis. The impacts of mining on land among other physical and chemical damage, erosion and widening the depth of the river, a pool of micro-climate, the quality and feasibility, vegetation, wildlife and biodiversity, land values, social and economic. This mining causes damage to the soil structure, and puddles in the former digs which were not backfilled again. The impact of mining on the ocean such as changes in current surge, erosion and abrasion basic coastal waters, shoreline change, marine water quality changes, and changes in marine communities. The findings of the research show that tin mining in the sea also potentially have a significant impact on the life of the reef, populations of marine organisms. However, mining on land needs to consider the impact of the damage, so that the damage can be minimized. In the recovery process needs to be pursued by exploiting the rest of the pile of tin. Thus, mining activities should take into account the distance of beach sediment size, wave height, wave length, wave period, and the acceleration of gravity. The process of the tin washing should be done in a fairly safe area, thus avoiding damage to the coral reefs that will eventually reduce the population of marine life. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=abration" title="abration">abration</a>, <a href="https://publications.waset.org/abstracts/search?q=environmental%20damage" title=" environmental damage"> environmental damage</a>, <a href="https://publications.waset.org/abstracts/search?q=mining" title=" mining"> mining</a>, <a href="https://publications.waset.org/abstracts/search?q=shoreline" title=" shoreline"> shoreline</a> </p> <a href="https://publications.waset.org/abstracts/61355/identification-of-environmental-damage-due-to-mining-area-bangka-islands-in-indonesia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61355.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">322</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">7505</span> Sequential Pattern Mining from Data of Medical Record with Sequential Pattern Discovery Using Equivalent Classes (SPADE) Algorithm (A Case Study : Bolo Primary Health Care, Bima)</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rezky%20Rifaini">Rezky Rifaini</a>, <a href="https://publications.waset.org/abstracts/search?q=Raden%20Bagus%20Fajriya%20Hakim"> Raden Bagus Fajriya Hakim</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research was conducted at the Bolo primary health Care in Bima Regency. The purpose of the research is to find out the association pattern that is formed of medical record database from Bolo Primary health care’s patient. The data used is secondary data from medical records database PHC. Sequential pattern mining technique is the method that used to analysis. Transaction data generated from Patient_ID, Check_Date and diagnosis. Sequential Pattern Discovery Algorithms Using Equivalent Classes (SPADE) is one of the algorithm in sequential pattern mining, this algorithm find frequent sequences of data transaction, using vertical database and sequence join process. Results of the SPADE algorithm is frequent sequences that then used to form a rule. It technique is used to find the association pattern between items combination. Based on association rules sequential analysis with SPADE algorithm for minimum support 0,03 and minimum confidence 0,75 is gotten 3 association sequential pattern based on the sequence of patient_ID, check_Date and diagnosis data in the Bolo PHC. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=diagnosis" title="diagnosis">diagnosis</a>, <a href="https://publications.waset.org/abstracts/search?q=primary%20health%20care" title=" primary health care"> primary health care</a>, <a href="https://publications.waset.org/abstracts/search?q=medical%20record" title=" medical record"> medical record</a>, <a href="https://publications.waset.org/abstracts/search?q=data%20mining" title=" data mining"> data mining</a>, <a href="https://publications.waset.org/abstracts/search?q=sequential%20pattern%20mining" title=" sequential pattern mining"> sequential pattern mining</a>, <a href="https://publications.waset.org/abstracts/search?q=SPADE%20algorithm" title=" SPADE algorithm"> SPADE algorithm</a> </p> <a href="https://publications.waset.org/abstracts/46321/sequential-pattern-mining-from-data-of-medical-record-with-sequential-pattern-discovery-using-equivalent-classes-spade-algorithm-a-case-study-bolo-primary-health-care-bima" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/46321.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">401</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=mining%20technique&page=2">2</a></li> <li class="page-item"><a class="page-link" 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