{"created":"2020-09-01T15:42:28.649251+00:00","id":5069,"links":{},"metadata":{"_buckets":{"deposit":"499645d4-2ea8-43c5-bc3c-b06c68642ba4"},"_deposit":{"id":"5069","owners":[],"pid":{"revision_id":0,"type":"recid","value":"5069"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/5069","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Analysis of Customer Buying Behavior using Equivalence Class Transformation (ECLAT)","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Many organizations are being interested inmining association rules from business recordsbecause they desire to promotethe benefit fromlarge amount of data that are continuously storedin databases. Discovery of frequent itemsetsthrough transactional records can support veryuseful idea and advice in business decisionmaking processes. Mining association rules fromtransactions is important in business calledmarket basket analysis. It helps the administrativelevel for making effective decisions.This system isintended to develop for analyzing the correlationof different items that are frequently buyingtogether in a grocery store. Equivalence ClassTransformation (ECLAT) is one of the bestalgorithms to identify which products arefrequently bought together.Such sets of associatedproducts can be used to optimize the offeredproducts on the displayed stands.Therefore, thissystem can give guide lines with valuable advicesto managers who are managing the arrangementof the items in grocery store."}]},"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":"2019-07-18"}],"displaytype":"preview","filename":"63_PDFsam_PSC_final proof.pdf","filesize":[{"value":"137 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/5069/files/63_PDFsam_PSC_final proof.pdf"},"version_id":"473e0d3e-c8af-4f70-bb04-52e7d02149ab"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Eighth 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":"Ei, Htet Htet"},{"subitem_authors_fullname":"Lwin, Wai Wai"}]}]},"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":"2017-12-27"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/960"},"item_title":"Analysis of Customer Buying Behavior using Equivalence Class Transformation (ECLAT)","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-18","publish_status":"0","recid":"5069","relation_version_is_last":true,"title":["Analysis of Customer Buying Behavior using Equivalence Class Transformation (ECLAT)"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T03:38:28.217578+00:00"}