{"created":"2020-09-01T13:38:36.206444+00:00","id":3842,"links":{},"metadata":{"_buckets":{"deposit":"cecc5f77-a09d-4774-9e55-068f65c2e862"},"_deposit":{"id":"3842","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3842"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3842","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Finding Association Rules from Sales Data with Apriori Algorithm","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"The association rule mining is one of the primary sub-areas in the field of data mining . This type of mining ,the association rule searches for interesting relation among item in a given data set , has been used in numerous practical applications : market basket analysis , catalog design and loss-leader analysis . In this paper, Apriori algorithm is implied for mining frequent itemsets for Boolean association rules with a large amount of items in a database. Consequently, every itemset is employed with level-wise search to provide achieving more frequent itemsets found. Furthermore , the user is eventually allowed to understand this system with two step process including join and prune actions. As a result, the valuable information is allowed to the user with a variety of threshold value. The association rule resulted from Apriori algorithm is also improved into strong rule according to these threshold values."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value":[]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-31"}],"displaytype":"preview","filename":"54164.pdf","filesize":[{"value":"347 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3842/files/54164.pdf"},"version_id":"8abda140-8b1d-4a4c-bea2-404be8793b72"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fourth Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Thein, Shwe Sin"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2009-12-30"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1568"},"item_title":"Finding Association Rules from Sales Data with Apriori Algorithm","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-31","publish_status":"0","recid":"3842","relation_version_is_last":true,"title":["Finding Association Rules from Sales Data with Apriori Algorithm"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T00:49:29.341901+00:00"}