{"_buckets": {"deposit": "d0a59666-0775-4ec7-881c-a0b69c852bc0"}, "_deposit": {"created_by": 45, "id": "6297", "owner": "45", "owners": [45], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "recid", "value": "6297"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/6297", "sets": ["user-uit"]}, "communities": ["uit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Community detection (CD) plays an important role in\nanalyzing social network features and helping to find out\nvaluable hidden information. Many research algorithms\nhave been proposed to find the best community in the\nnetwork. But it has many challenges such as scalability\nand time complexity. This paper proposes a new\nalgorithm, Artificial Bee Colony Algorithm with Genetic\nOperator (ABCGO) that combines crossover and\nmutation operators with Artificial Bee Colony algorithm.\nThis paper takes modularity Q as objective function.\nCompared with five state-of-art algorithms, results on\nreal world networks reflect the effectiveness of ABCGO."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Social Network"}, {"interim": "Community Detection"}, {"interim": "Artificial Bee Colony"}, {"interim": "Modularity"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-11-19"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator.pdf", "filesize": [{"value": "1.4 Mb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensefree": "© 2018 ICAIT", "licensetype": "license_free", "mimetype": "application/pdf", "size": 1400000.0, "url": {"url": "https://meral.edu.mm/record/6297/files/Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator.pdf"}, "version_id": "926ee1db-6b43-41f5-bc97-1f482d772d97"}]}, "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": "Data Mining", "subitem_website": "https://www.uit.edu.mm/icait-2018/"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Thet Thet Aung"}]}]}, "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": "Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator", "item_type_id": "21", "owner": "45", "path": ["1605779935331"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000006297", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-11-19"}, "publish_date": "2020-11-19", "publish_status": "0", "recid": "6297", "relation": {}, "relation_version_is_last": true, "title": ["Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator"], "weko_shared_id": -1}