{"created":"2020-11-26T08:55:32.054309+00:00","id":6638,"links":{},"metadata":{"_buckets":{"deposit":"fc8b9e02-fe75-4e60-a501-3e9e0963deff"},"_deposit":{"created_by":45,"id":"6638","owner":"45","owners":[45],"owners_ext":{"displayname":"","email":"dimennyaung@uit.edu.mm","username":""},"pid":{"revision_id":0,"type":"depid","value":"6638"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/00006638","sets":["1582963342780:1605779935331"]},"communities":["uit"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Feature Extraction Method for Aspect-Based Sentiment Analysis","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"In our daily life, we take opinions of our friends and we\nare influenced in decision making process. Opinion is\nthe view or the judgment about something. Opinion\nMining (OM) or Sentiment Analysis (SA) is the\ncomputational analysis of public’s opinion, emotion,\nsentiments, and attitude toward entities and their\nattributes expressed in written text. These entities may\nbe products, services, organizations, individuals, events,\nissues, or topics. In sentiment analysis, formal and\ninformal opinion text like product reviews, news\narticles, tweets, forum discussions, blogs, and Facebook\nposts are also applicable to all domains. The main\npurpose of sentiment analysis is to extract the main\nopinions, on which the decision can be made very right.\nPaper intends to classify sentiment polarity on product\nreview datasets by using Mutual Information as a\nfeature selection method. Because product reviews are\nhighly focused and they are opinion rich. After the\nfeature selection, we aim to classify the extracted\nfeatures with Naïve Bayes, SVM and Maximum Entropy\nto get the accurate sentiment polarity."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Sentiment Analysis"},{"interim":"Opinion Mining"},{"interim":"Feature Selection"},{"interim":"Feature Extraction"},{"interim":"Aspect-Based Sentiment Analysis"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2020-11-26"}],"displaytype":"preview","filename":"Feature Extraction Method for Aspect-Based Sentiment Analysis.pdf","filesize":[{"value":"375 Kb"}],"format":"application/pdf","licensetype":"license_0","url":{"url":"https://meral.edu.mm/api/files/fc8b9e02-fe75-4e60-a501-3e9e0963deff/Feature%20Extraction%20Method%20for%20Aspect-Based%20Sentiment%20Analysis.pdf"},"version_id":"e18e829a-a80c-4864-8e15-8d38daa606f5"}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"ICAIT-2017","subitem_c_date":"1-2 November, 2017","subitem_conference_title":"1st International Conference on Advanced Information Technologies","subitem_place":"Yangon, Myanmar","subitem_session":"Workshop Session","subitem_website":"https://www.uit.edu.mm/icait-2017/"}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Win Lei Kay Khine"},{"subitem_authors_fullname":"Nyein Thwet Thwet Aung"},{"subitem_authors_fullname":"Thet Thet Zin"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Conference paper"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2017-11-02"},"item_title":"Feature Extraction Method for Aspect-Based Sentiment Analysis","item_type_id":"21","owner":"45","path":["1605779935331"],"publish_date":"2020-11-26","publish_status":"0","recid":"6638","relation_version_is_last":true,"title":["Feature Extraction Method for Aspect-Based Sentiment Analysis"],"weko_creator_id":"45","weko_shared_id":-1},"updated":"2022-03-24T23:16:01.216541+00:00"}