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window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":108853635,"created_at":"2023-11-03T17:44:58.202-07:00","from_world_paper_id":242844586,"updated_at":"2024-11-24T02:29:41.095-08:00","_data":{"publisher":"Auricle Technologies Pvt., Ltd.","grobid_abstract":"This Market Basket Analysis (MBA) is a data mining technique that uses frequent pattern mining algorithms to discover patterns of co-occurrence among items that are frequently purchased together. It is commonly used in retail and e-commerce businesses to generate association rules that describe the relationships between different items, and to make recommendations to customers based on their previous purchases. MBA is a powerful tool for identifying patterns of co-occurrence and generating insights that can improve sales and marketing strategies. Although a numerous works has been carried out to handle the computational cost for discovering the frequent itemsets, but it still needs more exploration and developments. In this paper, we introduce an efficient Bitwise-Based data structure technique for mining frequent pattern in large-scale databases. The algorithm scans the original database once, using the Bitwise-Based data representations as well as vertical database layout, compared to the well-known Apriori and FP-Growth algorithm. Bitwise-Based technique enhance the problems of multiple passes over the original database, hence, minimizes the execution time. Extensive experiments have been carried out to validate our technique, which outperform Apriori, Éclat, FP-growth, and H-mine in terms of execution time for Market Basket Analysis.","publication_date":"2023,5,17","publication_name":"International Journal on Recent and Innovation Trends in Computing and Communication","grobid_abstract_attachment_id":"107135377"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"MBA: Market Basket Analysis Using Frequent Pattern Mining Techniques","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [56285868]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":107135377,"attachmentType":"pdf"}"><img alt="First page of “MBA: Market Basket Analysis Using Frequent Pattern Mining Techniques”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/107135377/mini_magick20231104-1-yaoacg.png?1699058735" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">MBA: Market Basket Analysis Using Frequent Pattern Mining Techniques</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="56285868" href="https://alazhari.academia.edu/SallamFageeri"><img alt="Profile image of Sallam Fageeri" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />Sallam Fageeri</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2023, International Journal on Recent and Innovation Trends in Computing and Communication</p><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">7 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 108853635; 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The purpose is to discover the concurrence association among data in large database & to discover interesting association between attributes in databases. The main aspect of ARM is to find frequent item set generation & Association Rule generation. In this paper we concentrate on frequent pattern mining Algorithms. This research paper discusses the comparison between three minig Algorithms i.e. Apriori Algorithm, Eclat Algorithm, and Improved Apriori Algorithm. It also focuses on advantages & disadvantages of these algorithms. The comparison is done w.r.t Market Basket Analysis using Hadoop. Mining of association rules from frequent pattern mining from massive collection of data is of interest for many industries which can provide guidance in decision making process such as cross marketing or arrangement of item in Stores & Supermarkets.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Comparative Study of Association Mining Algorithms for Market Basket Analysis","attachmentId":77031134,"attachmentType":"pdf","work_url":"https://www.academia.edu/65233623/A_Comparative_Study_of_Association_Mining_Algorithms_for_Market_Basket_Analysis","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/65233623/A_Comparative_Study_of_Association_Mining_Algorithms_for_Market_Basket_Analysis"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="61089935" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/61089935/Association_rule_with_frequent_pattern_growth_algorithm_for_frequent_item_sets_mining">Association rule with frequent pattern growth algorithm for frequent item sets mining</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="9923356" href="https://independent.academia.edu/KittipolWisaeng">Dr. Kittipol Wisaeng</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Applied Mathematical Sciences, 2014</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Association rule with frequent pattern growth algorithm for frequent item sets mining","attachmentId":74254287,"attachmentType":"pdf","work_url":"https://www.academia.edu/61089935/Association_rule_with_frequent_pattern_growth_algorithm_for_frequent_item_sets_mining","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/61089935/Association_rule_with_frequent_pattern_growth_algorithm_for_frequent_item_sets_mining"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="251611" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/251611/Market_Basket_Analysis_for_Data_Mining">Market Basket Analysis for Data Mining</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="208856" href="https://boun.academia.edu/Ayd%C4%B1nUla%C5%9F">Aydın Ulaş</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2001</p><p class="ds-related-work--abstract ds2-5-body-sm">Most of the established companies have accumulated masses of data from their customers for decades. With the e-commerce applications growing rapidly, the companies will have a significant amount of data in months not in years. Data Mining, also known as Knowledge Discovery in Databases (KDD), is to find trends, patterns, correlations, anomalies in these databases which can help us to make accurate future decisions. Mining Association Rules is one of the main application areas of Data Mining. Given a set of customer transactions on items, the aim is to find correlations between the sales of items. We consider Association Mining in large database of customer transactions. We give an overview of the problem and explain approaches that have been used to attack this problem. We then give the description of the Apriori Algorithm and show results that are taken from Gima Türk A.Ş. a large Turkish supermarket chain. We also use two statistical methods: Principal Component Analysis and k-means to detect correlations between sets of items.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Market Basket Analysis for Data Mining","attachmentId":37241584,"attachmentType":"pdf","work_url":"https://www.academia.edu/251611/Market_Basket_Analysis_for_Data_Mining","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/251611/Market_Basket_Analysis_for_Data_Mining"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="6608499" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/6608499/A_new_scheme_for_extracting_association_rules_market_basket_analysis_case_study">A new scheme for extracting association rules: market basket analysis case study</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="10681530" href="https://malaya.academia.edu/SooHyeZarZai">Soo Hye Zar Zai</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A new scheme for extracting association rules: market basket analysis case 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href="https://www.academia.edu/91240854/A_Systematic_Literature_Review_of_Frequent_Pattern_Mining_Techniques">A Systematic Literature Review of Frequent Pattern Mining Techniques</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="246401799" href="https://independent.academia.edu/HarishPatidar14">Harish Patidar</a></div><p class="ds-related-work--metadata ds2-5-body-xs">International Journal of Trend in Scientific Research and Development, 2018</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A Systematic Literature Review of Frequent Pattern Mining Techniques","attachmentId":94583788,"attachmentType":"pdf","work_url":"https://www.academia.edu/91240854/A_Systematic_Literature_Review_of_Frequent_Pattern_Mining_Techniques","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/91240854/A_Systematic_Literature_Review_of_Frequent_Pattern_Mining_Techniques"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="72549391" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/72549391/An_Efficient_Binary_to_Decimal_Conversion_Approach_for_Discovering_Frequent_Patterns">An Efficient Binary to Decimal Conversion Approach for Discovering Frequent Patterns</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="13056488" href="https://independent.academia.edu/KapilChaturvedi1">Kapil Chaturvedi</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2014</p><p class="ds-related-work--abstract ds2-5-body-sm">Association Rule Mining(ARM) is a most vital field of data mining to discover interesting relationship between items from huge transaction databases it analysis the data and discover strong rules using different measures such as (support, confidence, lift, conviction) etc, various ARM algorithms are available in literature for discovering frequent patterns. Market Basket analysis is one of the most essential applications of ARM; other applications are pattern recognition, weblog data mining and special data analysis etc. In this paper we proposed B2DCARM algorithm to discover frequent pattern which use Boolean matrix based technique. This algorithm adopts binary to decimal conversion approach to discover frequent itemsets from huge transaction database which outperforms in both of the cases where support threshold is low or high and also better performs from efficiency point of view compare to available tree based approaches.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"An Efficient Binary to Decimal Conversion Approach for Discovering Frequent Patterns","attachmentId":81434663,"attachmentType":"pdf","work_url":"https://www.academia.edu/72549391/An_Efficient_Binary_to_Decimal_Conversion_Approach_for_Discovering_Frequent_Patterns","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/72549391/An_Efficient_Binary_to_Decimal_Conversion_Approach_for_Discovering_Frequent_Patterns"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="8739344" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/8739344/Frequent_Pattern_and_Association_Rule_Mining_from_Inventory_Database_Using_Apriori_Algorithm">Frequent Pattern and Association Rule Mining from Inventory Database Using Apriori Algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="8929169" href="https://kwasu.academia.edu/SulaimanOlaniyiAbdulsalam">Sulaiman Olaniyi Abdulsalam</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Frequent Pattern and Association Rule Mining from Inventory Database Using Apriori Algorithm","attachmentId":35091140,"attachmentType":"pdf","work_url":"https://www.academia.edu/8739344/Frequent_Pattern_and_Association_Rule_Mining_from_Inventory_Database_Using_Apriori_Algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/8739344/Frequent_Pattern_and_Association_Rule_Mining_from_Inventory_Database_Using_Apriori_Algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="8739333" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/8739333/Data_Mining_in_Market_Basket_Transaction_An_Association_Rule_Mining_Approach">Data Mining in Market Basket Transaction: An Association Rule Mining Approach</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="8929169" href="https://kwasu.academia.edu/SulaimanOlaniyiAbdulsalam">Sulaiman Olaniyi Abdulsalam</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Data Mining in Market Basket Transaction: An Association Rule Mining Approach","attachmentId":35091128,"attachmentType":"pdf","work_url":"https://www.academia.edu/8739333/Data_Mining_in_Market_Basket_Transaction_An_Association_Rule_Mining_Approach","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/8739333/Data_Mining_in_Market_Basket_Transaction_An_Association_Rule_Mining_Approach"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="83804620" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" 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