{"_buckets": {"deposit": "22694032-c530-4915-87bd-148686550a6b"}, "_deposit": {"id": "4674", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4674"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4674", "sets": ["1597824273898", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Myanmar Spam Filtering based on Naïve Bayesian Learning Algorithm (MSFNBLA)", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Spam is one of the main problems in e-mailscommunication. Naïve Bayesian (NB) learning isuseful algorithm for constructing Myanmarspam corpus (SCorpus) from pre-defined spamand ham e-mails. SCorpus is built on theassumption that the characteristics of e-mails inthe training dataset. Content-based analysis isparticularly effective in filtering spam. NB playsa critical role in probabilistic learning andcalculates the probability of an e-mail beingspam based on its contents. The motivation forthis paper is to find a solution for the Internetusers in Myanmar e-mails received every day intheir mailboxes. There is no standardimplementation for treatment of Myanmar emails.So, a classification filter for the e-mailsshould be proposed with SCorpus. NB approachis being popular for learning corpus. To filter thespam e-mail, paper MSFNBLA is applied forclassifying the incoming e-mail is spam or ham."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Spam e-mail filtering"}, {"interim": "Spam"}, {"interim": "NB learning algorithm"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value": []}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fourteenth International Conference On Computer Applications (ICCA 2016)", "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": "Nyo, Nyein Nyein"}, {"subitem_authors_fullname": "Kyaw, Thae Naw Naw"}]}]}, "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": "2016-02-25"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/334"}, "item_title": "Myanmar Spam Filtering based on Naïve Bayesian Learning Algorithm (MSFNBLA)", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004674", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-03"}, "publish_date": "2019-07-03", "publish_status": "0", "recid": "4674", "relation": {}, "relation_version_is_last": true, "title": ["Myanmar Spam Filtering based on Naïve Bayesian Learning Algorithm (MSFNBLA)"], "weko_shared_id": -1}