{"updated":"2025-01-21T12:55:36.615586+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00097181","sets":["6164:6165:6640:7359"]},"path":["7359"],"owner":"11","recid":"97181","title":["確率的訪問POI分析: 時空間行動軌跡からのユーザモデリング"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-07-03"},"_buckets":{"deposit":"8004b61b-d5c5-48b9-9ce9-deae0b09b1ab"},"_deposit":{"id":"97181","pid":{"type":"depid","value":"97181","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"確率的訪問POI分析: 時空間行動軌跡からのユーザモデリング","author_link":["0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"確率的訪問POI分析: 時空間行動軌跡からのユーザモデリング"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"位置情報システム","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2013-07-03","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"日本電信電話株式会社NTTサービスエボリューション研究所"},{"subitem_text_value":"日本電信電話株式会社NTTサービスエボリューション研究所"},{"subitem_text_value":"日本電信電話株式会社NTTサービスエボリューション研究所"},{"subitem_text_value":"日本電信電話株式会社NTTサービスエボリューション研究所"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/97181/files/IPSJ-DICOMO2013052.pdf"},"date":[{"dateType":"Available","dateValue":"2013-07-03"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2013052.pdf","filesize":[{"value":"3.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"0de57f22-ee80-495c-994a-666c6ebf4b6e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2013 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"西田京介"},{"creatorName":"戸田浩之"},{"creatorName":"倉島健"},{"creatorName":"内山匡"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"GPSやネットワーク位置情報源（携帯基地局やWi-Fiなど）により得られるユーザの時空間行動軌跡から，そのユーザが訪問した場所（Point of Interest; POI）を推定する確率的訪問POI分析技術を提案する．提案技術は（1）時空間カーネルを用いたMean-shiftクラスタリングによる滞留点抽出法（2）ユーザの真の訪問POIを潜在変数とした，滞留点の位置とその滞留時間に関する確率的生成モデル，から構成され，真の訪問POIが未知の滞留データも学習に利用することで訪問POIを高精度に推定できる．本技術が実現する訪問POIを基にした個々のユーザの行動・嗜好の理解は，情報提供や生活支援などパーソナルアシスタントサービスの品質向上に貢献できる．本論文では，GPS/Wi-FIにより得られた実データによる実験を行い，提案技術が従来手法に比べて滞留点の抽出と訪問POIの推定を精度良く行えたことを示す．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"345","bibliographic_titles":[{"bibliographic_title":"マルチメディア、分散協調とモバイルシンポジウム2013論文集"}],"bibliographicPageStart":"334","bibliographicIssueDates":{"bibliographicIssueDate":"2013-07-03","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2013"}]},"relation_version_is_last":true,"item_18_alternative_title_2":{"attribute_name":"その他タイトル","attribute_value_mlt":[{"subitem_alternative_title":"グループウェアとネットワークサービス"}]},"weko_creator_id":"11"},"created":"2025-01-18T23:43:43.900731+00:00","id":97181,"links":{}}