{"created":"2020-09-01T13:12:31.830490+00:00","id":3614,"links":{},"metadata":{"_buckets":{"deposit":"eae4c613-669d-4978-be72-a11f7b5617a7"},"_deposit":{"id":"3614","owners":[],"pid":{"revision_id":0,"type":"recid","value":"3614"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/3614","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Data Clustering using Ant Clustering Algorithm (ACA)","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Clustering refers to the grouping of data records, observation orcases into similar objects. A cluster observation or cases similar to one another, anddissimilar to the record in other cluster. Recently, much research has been proposedusing nature inspired algorithm to perform complex machine learning task such asclustering. Clustering with swarm-based algorithms is emerging as an alternativeto more conventional clustering techniques. Ant colonies have been observed toperform tasks similar to clustering. This observation is the inspiration of ant basedclustering algorithm, which simulated the behavior on the data. There are manyadvantages to ant clustering than conventional clustering algorithm such as KMeanssuch that ant clustering algorithm can automatically discover number ofcluster and they are suitable for large and high dimensional dataset due to theirgrid based sorting nature. This paper presents the implementation of the ant basedclustering algorithm for clustering data on various dataset and providesexperimental results."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value":[]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-07-26"}],"displaytype":"preview","filename":"Data Clustering using Ant Clustering Algorithm.pdf","filesize":[{"value":"7 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/3614/files/Data Clustering using Ant Clustering Algorithm.pdf"},"version_id":"c75d88a3-e4a4-458f-b532-d2039efe8877"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Sixth Local Conference on Parallel and Soft Computing","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":"Htwe, Lei Yi"},{"subitem_authors_fullname":"Phyu, Aye Lei Lei"}]}]},"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":"2011-12-29"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1348"},"item_title":"Data Clustering using Ant Clustering Algorithm (ACA)","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-07-26","publish_status":"0","recid":"3614","relation_version_is_last":true,"title":["Data Clustering using Ant Clustering Algorithm (ACA)"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2022-03-24T23:15:58.483709+00:00"}