{"created":"2020-11-20T05:01:10.569236+00:00","id":6342,"links":{},"metadata":{"_buckets":{"deposit":"d9bc3dca-e071-4eb6-ba92-7a5478205d0d"},"_deposit":{"created_by":45,"id":"6342","owner":"45","owners":[45],"owners_ext":{"displayname":"","email":"dimennyaung@uit.edu.mm","username":""},"pid":{"revision_id":0,"type":"recid","value":"6342"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/6342","sets":["1582963342780:1605779935331"]},"communities":["uit"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Myanmar Semantic Information Retrieval Using Self Organizing Map with Global Vector – MyanSeM","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Nowadays, explosive growing the resources with Myanmar language on the Internet, the information retrieval (IR) for Myanmar web pages has increasingly important.The proposed system presents an effective semantic retrieval approach based on parallel Self Organizing Map (SOM), which uses document associationinstead of Euclidian distance in distance calculation, and GloVe (Global Vector for Word Representation) for word co-occurrence. The Self Organizing Map (SOM) has been a promising method for document clustering and word sense disambiguation. This approach uses the parallel training the separate parts of SOM for document clustering, then combine, and re-cluster the documents.During the training of the parts of SOM, global vector is used for appearance of word co-occurrence and then combines the word categories based on semantic sense.Although many researchers have researched the various semantic information retrieval approaches, they have not yet adapted to retrieve the semantic information of Myanmar words and sentences. This approach can retrieve most semantically relevant web documents. This does not take too long time for SOM training because of parallel GPU approach."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value_mlt":[{"interim":"Semantic Web"},{"interim":"Self-Organizing Map"},{"interim":"Information Retrieval"}]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2020-11-20"}],"displaytype":"preview","filename":"Myanmar Semantic Information Retrieval Using Self Organizing Map with Global Vector – MyanSeM.pdf","filesize":[{"value":"1.8 Mb"}],"format":"application/pdf","license_note":"© 2018 ICAIT","licensetype":"license_note","url":{"url":"https://meral.edu.mm/record/6342/files/Myanmar Semantic Information Retrieval Using Self Organizing Map with Global Vector – MyanSeM.pdf"},"version_id":"0cc097ee-ddb0-411b-85ad-88050dd29994"}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"ICAIT-2018","subitem_c_date":"1-2 November, 2018","subitem_conference_title":"2nd International Conference on Advanced Information Technologies","subitem_place":"Yangon, Myanmar","subitem_session":"Simulation and Modeling in Software Approach","subitem_website":"https://www.uit.edu.mm/icait-2018/"}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Thiri Haymar Kyaw"},{"subitem_authors_fullname":"Thinn Thinn Wai"},{"subitem_authors_fullname":"Thinn Mya Mya Swe"}]}]},"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":"2018-11-02"},"item_title":"Myanmar Semantic Information Retrieval Using Self Organizing Map with Global Vector – MyanSeM","item_type_id":"21","owner":"45","path":["1605779935331"],"publish_date":"2020-11-20","publish_status":"0","recid":"6342","relation_version_is_last":true,"title":["Myanmar Semantic Information Retrieval Using Self Organizing Map with Global Vector – MyanSeM"],"weko_creator_id":"45","weko_shared_id":-1},"updated":"2021-12-13T00:26:42.580678+00:00"}