{"_buckets": {"deposit": "cedc0f63-374d-4feb-96fb-284b9038fb62"}, "_deposit": {"id": "4771", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4771"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4771", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Moving Objects Clustering from Big Trajectory Data", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "The mobile communication technologiespenetrate our society and wireless network to detectthe movement of people to generate large amount ofdata mobility including mobile phone call recordsand Global Positioning System (GPS) traces whichcan be characterized as big trajectory data. Theremarkable analytical strength of the massive datacollection trajectory can help to show the complexityof human mobility. The knowledge discovery processis addressed on some of the fundamental issues ofmobility analysts such as the ways people move. Inthis work, the problem of determining the number ofgroups and the members of the trajectory nodeswithin the group from big trajectory data areconsidered. A framework for clustering movingobjects from big trajectory data is designed.Additionally, a distance based clustering algorithm tospecify the number of groups and their identity areproposed. Finally, the proposed methods arepractically evaluated using real Geolife dataset."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "GPS"}, {"interim": "Moving Objects"}, {"interim": "Big Trajectory Data"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value": []}, "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": "Wai, Khaing Phyo"}, {"subitem_authors_fullname": "Nwe, Nwe"}]}]}, "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/123456789/660"}, "item_title": "Moving Objects Clustering from Big Trajectory Data", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004771", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-09"}, "publish_date": "2019-07-09", "publish_status": "0", "recid": "4771", "relation": {}, "relation_version_is_last": true, "title": ["Moving Objects Clustering from Big Trajectory Data"], "weko_shared_id": -1}