{"_buckets": {"deposit": "b3feeaff-7ab8-4992-87fd-a27e642f2a47"}, "_deposit": {"id": "4521", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4521"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4521", "sets": ["1597824273898", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "MoveMine: Moving Object Trajectory Clustering", "subitem_1551255648112": "en_US"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "With the maturity of GeographicalPositioning System (GPS), wireless, and Webtechnologies, increasing amounts of movementdata collected from various moving objects, suchas animals, vehicles, mobile devices, and climateradars, has become widely available. Analyzingsuch data has broad applications, such as, inecological study, vehicle control, mobilecommunication management, and climatologicalforecast. MoveMine is designed for sophisticatedmoving object data mining by integrating severalattractive functions including moving objectpattern mining and trajectory mining. Trajectoryclustering is one of the major functions intrajectory mining. Existing trajectory clusteringalgorithms group similar trajectories as a whole,thus discovering common trajectories. In thispaper, moving object trajectory clustering ispresented. In trajectory segmentation, the globaloptimum segmentation can be found by dynamicprogramming. We present a pattern basedclustering algorithm that extends k-meansalgorithm for clustering moving object trajectorydata. The system will be evaluated on elk, deerand cattle’s movement dataset which has beengenerated by the Starkey project for effectivenessof the system."}]}, "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": "2019-11-15"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "10102.pdf", "filesize": [{"value": "813 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 813000.0, "url": {"url": "https://meral.edu.mm/record/4521/files/10102.pdf"}, "version_id": "d0942824-0c26-444f-aa9a-6c0c127ef17e"}]}, "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"}]}]}, "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/123456789/2446"}, "item_title": "MoveMine: Moving Object Trajectory Clustering", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004521", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-11-15"}, "publish_date": "2019-11-15", "publish_status": "0", "recid": "4521", "relation": {}, "relation_version_is_last": true, "title": ["MoveMine: Moving Object Trajectory Clustering"], "weko_shared_id": -1}