{"_buckets": {"deposit": "4917584e-25c2-49de-b058-4d09feca2be7"}, "_deposit": {"id": "4984", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4984"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4984", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "An Implementation of Naive Bayesian based Bagging Method for Advertisements Prediction", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Nowadays, the field of advertising is morespread. Broadcasting media receives advertisementsfrom advertisement companies. When programmeare shown, these advertisements used to bebroadcasted. Most of the advertisement companiesinstall to broadcast its advertisements whenadvertisement time. As Myanmar rule, it must bebroadcasted one third of the programme. So, mediacannot receive all advertisements. By using thissystem, it is easy to know which advertisementcompanies should be imperative if new programmebroadcast. In this system, Bagging and NaiveBayesian Classification methods are used. Baggingmethod is one of the well-known ensemble techniquesthat build bags of data of the same size of theoriginal data sets by applying random sampling withreplacement. Naive Bayesian Classification methodis widely used for probabilities estimations. Usingthe mixture of these algorithms, we get theprobabilities from multiple models .Then, averagingprobability values are calculated with baggingmethod. Finally, the system extracts the companynames with highest probabilities. Companies can beclassified into \u0026quot;classes\u0026quot;. Another way, users can viewproducts information and reports at different sites.No need to look large amount of historical data."}]}, "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": "2019-07-12"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "psc2010paper (149).pdf", "filesize": [{"value": "65 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 65000.0, "url": {"url": "https://meral.edu.mm/record/4984/files/psc2010paper (149).pdf"}, "version_id": "91a6e822-052f-4aad-9212-385dab4549bb"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fifth 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": "Maung, Moh Cherry"}, {"subitem_authors_fullname": "Tun, Myat Thuzar"}]}]}, "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": "2010-12-16"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/881"}, "item_title": "An Implementation of Naive Bayesian based Bagging Method for Advertisements Prediction", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004984", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-12"}, "publish_date": "2019-07-12", "publish_status": "0", "recid": "4984", "relation": {}, "relation_version_is_last": true, "title": ["An Implementation of Naive Bayesian based Bagging Method for Advertisements Prediction"], "weko_shared_id": -1}