{"created":"2020-09-01T15:37:08.826495+00:00","id":4995,"links":{},"metadata":{"_buckets":{"deposit":"d17f6da5-91c7-4e17-ae15-161ca108746b"},"_deposit":{"id":"4995","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4995"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4995","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Exploring Features for Myanmar Named Entity Recognition","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Named Entity Recognition (NER) is the task ofclassifying or labeling atomic elements in the text intopredefined sets of named entity categories such asPerson, Location, Organization or Number. NER isalso a crucial piece of Information Extraction System.Robust handling of proper names is essential for manyapplications in natural language processing and keyknowledge acquisition infrastructure for the SemanticWeb. For Myanmar Language, exploring features forNER with machine learning approach is a stillchallenging task because of the complex nature of thelanguage. This paper describes our effort on featureexploring using local and external information forMyanmar NER that applied Conditional RandomFields (CRFs). The experimental results show that thebest result is obtained by combining the local feature,such as neighboring words, and the externalinformation such as clue words and name lists."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Named Entity Recognition"},{"interim":"Feature Exploring"},{"interim":"Myanmar Language"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-15"}],"displaytype":"preview","filename":"proceeding_total-pages-429-433.pdf","filesize":[{"value":"3105 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4995/files/proceeding_total-pages-429-433.pdf"},"version_id":"f6ffa788-4142-40b8-b659-2be685f49f02"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fifteenth International Conference on Computer Applications(ICCA 2017)","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":"Mo, Hsu Myat"},{"subitem_authors_fullname":"Nwet, Khin Thandar"},{"subitem_authors_fullname":"Soe, Khin Mar"}]}]},"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":"2017-02-16"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/892"},"item_title":"Exploring Features for Myanmar Named Entity Recognition","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-15","publish_status":"0","recid":"4995","relation_version_is_last":true,"title":["Exploring Features for Myanmar Named Entity Recognition"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T02:42:31.843468+00:00"}