{"_buckets": {"deposit": "63930aa2-ccb2-4687-877f-7c8141e7f297"}, "_deposit": {"id": "4719", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4719"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4719", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Vehicle Trajectory Analysis by Clustering", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "With widespread availability of low cost GPSdevices, it is becoming possible to record data about themoving objects on a large scale. The analysis of movingobjects trajectory data is a critical component in a widerange of research and decision-making fields. Toanalyze the object movement regularities and anomalies,trajectory clustering plays an important role intrajectory mining. Trajectory clustering provides newand helpful information such as Jam detection andsignificant location recognition. In this paper, we focuson vehicle movement trajectory data and analyze todiscover the various significant locations. We propose aK-means based clustering algorithm to mine thetrajectory data for extracting the important information.The truck trajectory dataset of Athens is used in theproposed approach as an illustrative example. The resultof clustering is visualized with the help of Google Maps."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "K-means clustering"}, {"interim": "move mining"}, {"interim": "trajectory clustering"}, {"interim": "vehicle movement data analysis"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value": []}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Tenth International Conference On Computer Applications (ICCA 2012)", "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": "Khaing, Hnin Su"}, {"subitem_authors_fullname": "Thein, Thandar"}]}]}, "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": "2012-02-28"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/425"}, "item_title": "Vehicle Trajectory Analysis by Clustering", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004719", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-04"}, "publish_date": "2019-07-04", "publish_status": "0", "recid": "4719", "relation": {}, "relation_version_is_last": true, "title": ["Vehicle Trajectory Analysis by Clustering"], "weko_shared_id": -1}