{"created":"2020-09-01T14:59:56.680804+00:00","id":4514,"links":{},"metadata":{"_buckets":{"deposit":"7c47d404-645e-407c-84f8-96a09d4bef5d"},"_deposit":{"id":"4514","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4514"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4514","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Comparative Analysis of Web Usage Data Clustering Using Asymmetric Binary Variables and K-Means","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"World Wide Web overwhelms us with theimmense amounts of widely distributedinterconnected, rich and dynamic information. As aconsequence of this, Web Usage Mining becomes oneof the popular research areas. It involves theapplication of data mining techniques to discoverusage patterns from the Web access logs data.Clustering is one of the important functions in WebUsage Mining to group the user access patterns whichhave the same access behavior. In this paper, wewould like to propose a new approach, asymmetricbinary variables (one type of Jaccard coefficient) toperform clustering. And then the performance of ourproposed approach is compared with k-meansclustering. The resulting clusters from these twomethods are tested with two internal validationmethods: Dunn Index and DB Index (Davies andBouldin Index). Finally, we point out the strengths andweaknesses of each method. According to the analysisresults, the findings of clustering upon these methodscan be seen clearly."}]},"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":"2019-07-03"}],"displaytype":"preview","filename":"9084.pdf","filesize":[{"value":"53 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4514/files/9084.pdf"},"version_id":"e4ce4394-6586-4e94-ba3e-afd73b61705c"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Ninth International Conference On Computer Applications (ICCA 2011)","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":"Shwe, Theint Theint"}]}]},"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":"2011-05-05"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/244"},"item_title":"Comparative Analysis of Web Usage Data Clustering Using Asymmetric Binary Variables and K-Means","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-03","publish_status":"0","recid":"4514","relation_version_is_last":true,"title":["Comparative Analysis of Web Usage Data Clustering Using Asymmetric Binary Variables and K-Means"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T02:04:22.766998+00:00"}