{"_buckets": {"deposit": "82b38414-281b-452e-a0be-7488bbcee9c6"}, "_deposit": {"id": "5063", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "5063"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/5063", "sets": ["1597824273898", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Enhanced Matrix based Frequent Accessed Pages Mining Algorithm", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "In computer science and Web miningwhich is an interdisciplinary subfield of computerscience, is the computational process ofdiscovering patterns in web log files. The overallgoal of the web mining process is to extractinformation from web log files and transform itinto an understandable structure for further use.In Web mining, Apriori is a classic algorithm forlearning association rules. This classicalalgorithm is inefficient due to so many scans ofdatabase and takes too much time to scan thedatabase. In this paper we will build a method toobtain the frequent page-item set by using adifferent approach to the classical Apriorialgorithm but based on it and applying theconcept of transaction reduction and a new matrixmethod."}]}, "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", "download_preview_message": "", "file_order": 0, "filename": "58_PDFsam_PSC_final proof.pdf", "filesize": [{"value": "137 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 137000.0, "url": {"url": "https://meral.edu.mm/record/5063/files/58_PDFsam_PSC_final proof.pdf"}, "version_id": "a841ec79-9f7f-4d52-98b6-e18866a1c4d8"}]}, "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": "Aung, Tharyar"}, {"subitem_authors_fullname": "Tun, Khin Nwe Ni"}]}]}, "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/123456789/955"}, "item_title": "Enhanced Matrix based Frequent Accessed Pages Mining Algorithm", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000005063", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-18"}, "publish_date": "2019-07-18", "publish_status": "0", "recid": "5063", "relation": {}, "relation_version_is_last": true, "title": ["Enhanced Matrix based Frequent Accessed Pages Mining Algorithm"], "weko_shared_id": -1}