{"created":"2023-06-20T12:59:56.934428+00:00","id":4020,"links":{},"metadata":{"_buckets":{"deposit":"60322b8e-ab65-4120-ae2a-4bb64ef4e240"},"_deposit":{"created_by":2,"id":"4020","owners":[2],"pid":{"revision_id":0,"type":"depid","value":"4020"},"status":"published"},"_oai":{"id":"oai:fun.repo.nii.ac.jp:00004020","sets":["22:28","25:81:101"]},"author_link":["7216","7218","95","7217"],"item_5_biblio_info_5":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2008","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"20","bibliographicPageStart":"11","bibliographic_titles":[{"bibliographic_title":"Neural Information Processing -Letters and Reviews"}]}]},"item_5_description_3":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"株式会社リコーとの共同研究を論文化した論文である．各個人の行動の予測を行う予測器を協調アンサンブルさせることで効果的な機能推薦を行うためのシステムを提案した．通常のベイズによる予測器アンサンブルはカルバック-ライブラーダイバージェンスの重み付き和の最小化として定式化されるが，本論文ではα-ダイバージェンスを用いることで新たな推薦システムを提案した．結果，各予測器の協調の度合いを制御することが可能となり，状況に応じて柔軟な推薦を行うことが可能となった．","subitem_description_type":"Abstract"}]},"item_5_select_10":{"attribute_name":"単著共著","attribute_value_mlt":[{"subitem_select_item":"共著/joint"}]},"item_5_select_8":{"attribute_name":"査読有無","attribute_value_mlt":[{"subitem_select_item":"あり/yes"}]},"item_5_select_9":{"attribute_name":"研究業績種別","attribute_value_mlt":[{"subitem_select_item":"原著論文/Original Paper"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hirayama, Jun-ichiro"}],"nameIdentifiers":[{"nameIdentifier":"7216","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Nakatomi, M."}],"nameIdentifiers":[{"nameIdentifier":"7217","nameIdentifierScheme":"WEKO"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"","affiliationNameIdentifierScheme":"ISNI","affiliationNameIdentifierURI":"http://www.isni.org/isni/"}],"affiliationNames":[{"affiliationName":"","affiliationNameLang":"ja"}]}],"creatorNames":[{"creatorName":"竹之内, 高志","creatorNameLang":"ja"}],"familyNames":[{"familyName":"竹之内","familyNameLang":"ja"}],"givenNames":[{"givenName":"高志","givenNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"95","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"50403340","nameIdentifierScheme":"e-Rad","nameIdentifierURI":"https://kaken.nii.ac.jp/ja/search/?qm=50403340"}]},{"creatorNames":[{"creatorName":"Ishii, Shin"}],"nameIdentifiers":[{"nameIdentifier":"7218","nameIdentifierScheme":"WEKO"}]}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"α-Bayesian collaboration of multiple predictors and its applications to hybrid recommendation and user modeling","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"α-Bayesian collaboration of multiple predictors and its applications to hybrid recommendation and user modeling"}]},"item_type_id":"5","owner":"2","path":["28","101"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-04-15"},"publish_date":"2013-04-15","publish_status":"0","recid":"4020","relation_version_is_last":true,"title":["α-Bayesian collaboration of multiple predictors and its applications to hybrid recommendation and user modeling"],"weko_creator_id":"2","weko_shared_id":-1},"updated":"2025-02-07T05:09:02.861180+00:00"}