{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00236340","sets":["6504:11678:11688"]},"path":["11688"],"owner":"44499","recid":"236340","title":["Enhancing Prediction of Next Points of Interest Using Self-Supervised Contrastive Learning"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"91e1c68b-b1af-4fb6-a86a-aae427735f94"},"_deposit":{"id":"236340","pid":{"type":"depid","value":"236340","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Enhancing Prediction of Next Points of Interest Using Self-Supervised Contrastive Learning","author_link":["645988","645989","645987"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Enhancing Prediction of Next Points of Interest Using Self-Supervised Contrastive Learning"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ネットワーク","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2024-03-01","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東工大"},{"subitem_text_value":"関東学院大"},{"subitem_text_value":"東工大"}]},"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/236340/files/IPSJ-Z86-7D-05.pdf","label":"IPSJ-Z86-7D-05.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-04"}],"format":"application/pdf","filename":"IPSJ-Z86-7D-05.pdf","filesize":[{"value":"212.0 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"1885d650-4e05-4057-9ba0-e7c3973f3782","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"韓, 秋涵"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"吉川, 厚"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山村, 雅幸"}],"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_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"In recent years, the ubiquitous GPS-equipped mobile devices have substantially advanced the research on personalized user mobility patterns through location data. However, accurately predicting Points of Interest (POIs) remains challenging in scenarios with sparse data. This study addresses such challenges by employing a self-supervised contrastive learning approach, which utilizes the adjacency matrices of locations within cities to predict users' subsequent POIs. This method not only improves prediction accuracy where data is limited but also sets the stage for innovative applications in deciphering human mobility and enhancing personalized services.","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"46","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"45","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":236340,"updated":"2025-01-19T09:17:56.533036+00:00","links":{},"created":"2025-01-19T01:38:20.257559+00:00"}