{"_buckets": {"deposit": "fc5c7257-07ce-4cb1-9a35-29d45f1e1648"}, "_deposit": {"id": "4473", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4473"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4473", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Predicting Web Interface Quality Assessment Using Support Vector Machine", "subitem_1551255648112": "en_US"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Internet websites are promising as theproducts for providing services. The key issuesrelated to website engineering are very essential.These websites need to measure and evaluate forquality and for better understanding. SeveralMetrics were proposed to correspond with itemsthat Web usability guideline associate with gooddesign. In this paper, we investigate empiricallythe web page quality on the basis of the 16assessed metrics. We also propose SupportVector Machine (SVM) prediction model topredict the classification of the good web pagesand not good web pages. We collect web sitesfrom Webby awards data (2001-2010) and TopTen PC Magazines. We express the findings ofquantitative analysis of web page attributes andhow these attributes are calculated. The metricscaptured in SVM model can be used to predictthe good and the bad of website design."}]}, "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": "2019-11-14"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "10046.pdf", "filesize": [{"value": "628 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 628000.0, "url": {"url": "https://meral.edu.mm/record/4473/files/10046.pdf"}, "version_id": "b4d2bdf5-7135-4feb-8ab9-b454a73edb5c"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Tenth International Conference On Computer Applications (ICCA 2012)", "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": "Wah, Naw Lay"}]}]}, "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": "2012-02-28"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/2402"}, "item_title": "Predicting Web Interface Quality Assessment Using Support Vector Machine", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004473", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-11-14"}, "publish_date": "2019-11-14", "publish_status": "0", "recid": "4473", "relation": {}, "relation_version_is_last": true, "title": ["Predicting Web Interface Quality Assessment Using Support Vector Machine"], "weko_shared_id": -1}