{"updated":"2025-01-21T17:02:01.090449+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00087802","sets":["1164:3500:6967:6968"]},"path":["6968"],"owner":"11","recid":"87802","title":["Extended Bayesian Model for Multi-criteria Recommender System"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-01-04"},"_buckets":{"deposit":"6f2926c2-2c01-4da6-8c63-3f6a668e44e9"},"_deposit":{"id":"87802","pid":{"type":"depid","value":"87802","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"Extended Bayesian Model for Multi-criteria Recommender System","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Extended Bayesian Model for Multi-criteria Recommender System"},{"subitem_title":"Extended Bayesian Model for Multi-criteria Recommender System","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2013-01-04","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"The Graduated University for Advanced Study"},{"subitem_text_value":"National Institute of Informatics／The Graduated University for Advanced Study"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"The Graduated University for Advanced Study","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Informatics / The Graduated University for Advanced Study","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/87802/files/IPSJ-IFAT13109006.pdf"},"date":[{"dateType":"Available","dateValue":"2015-01-04"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-IFAT13109006.pdf","filesize":[{"value":"244.2 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"39"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"c10bc600-af0c-44d9-879e-c14dd4a9ba5d","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2013 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Pannawit, Samatthiyadikun"},{"creatorName":"Atsuhiro, Takasu"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Pannawit, Samatthiyadikun","creatorNameLang":"en"},{"creatorName":"Atsuhiro, Takasu","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10114171","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"We have proposed multi-criteria (MC) recommender system by using a latent probabilistic model. In this model, users and items are mapped into small number of groups, and preference is represented based on the group instead of indivisual user. In other words, features of users and items are represented by probability distributions over latent topics. When predicting rating scores, we need to aggregate features into predicted rating score. This paper compares two ways to aggregate features for predicting rating score of unrated items in MC recommendation.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We have proposed multi-criteria (MC) recommender system by using a latent probabilistic model. In this model, users and items are mapped into small number of groups, and preference is represented based on the group instead of indivisual user. In other words, features of users and items are represented by probability distributions over latent topics. When predicting rating scores, we need to aggregate features into predicted rating score. This paper compares two ways to aggregate features for predicting rating score of unrated items in MC recommendation.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告情報基礎とアクセス技術（IFAT）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2013-01-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicVolumeNumber":"2013-IFAT-109"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-18T23:38:24.271941+00:00","id":87802,"links":{}}