{"created":"2020-09-01T13:56:45.572226+00:00","id":4027,"links":{},"metadata":{"_buckets":{"deposit":"7cff9f1d-3601-41f7-bdf5-4ba005f31f54"},"_deposit":{"id":"4027","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4027"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4027","sets":["1582963302567:1597824175385"]},"communities":["ucsy"],"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 inanalyzing social network features and helping to find outvaluable hidden information. Many research algorithmshave been proposed to find the best community in thenetwork. But it has many challenges such as scalabilityand time complexity. This paper proposes a newalgorithm, Artificial Bee Colony Algorithm with GeneticOperator (ABCGO) that combines crossover andmutation operators with Artificial Bee Colony algorithm.This paper takes modularity Q as objective function.Compared with five state-of-art algorithms, results onreal 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":"2019-08-05"}],"displaytype":"preview","filename":"Community Detection in Social Network Using Artificial Bee Colony with Genetic.pdf","filesize":[{"value":"1352 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4027/files/Community Detection in Social Network Using Artificial Bee Colony with Genetic.pdf"},"version_id":"88956997-b542-42b6-94c4-4f5507f86a2d"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Second International Conference on Advanced Information Technologies (ICAIT 2018)","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":"Aung, Thet Thet"},{"subitem_authors_fullname":"Nyunt, Thi Thi Soe"}]}]},"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":"2018-11-01"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1737"},"item_title":"Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator","item_type_id":"21","owner":"1","path":["1597824175385"],"publish_date":"2019-08-05","publish_status":"0","recid":"4027","relation_version_is_last":true,"title":["Community Detection in Social Network Using Artificial Bee Colony with Genetic Operator"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T01:22:18.484687+00:00"}