{"created":"2021-03-01T06:01:00.491190+00:00","id":8679,"links":{},"metadata":{"_buckets":{"deposit":"f148d37f-c2f6-4fb8-bceb-e8d898c44e1c"},"_deposit":{"id":"8679","owners":[],"pid":{"revision_id":0,"type":"depid","value":"8679"},"status":"published"},"_oai":{"id":"oai:kitami-it.repo.nii.ac.jp:00008679","sets":["1:86"]},"author_link":["273","90064","89671","90082","7687","90067","7691","9451"],"item_1646810750418":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_3_alternative_title_198":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"Semi-supervised Learning for a New Customer Problem in Recommender System","subitem_alternative_title_language":"en"}]},"item_3_biblio_info_186":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2018-05","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicPageEnd":"46","bibliographicPageStart":"37","bibliographicVolumeNumber":"20","bibliographic_titles":[{"bibliographic_title":"バイオメディカル・ファジィ・システム学会誌"},{"bibliographic_title":"Journal of Biomedical Fuzzy Systems Association","bibliographic_titleLang":"en"}]}]},"item_3_description_184":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"従来研究では，推薦システムの新規顧客問題を表現するための確率モデルとしてマルコフ決定過程が採用され，マルコフ決定過程の真のパラメータが既知の仮定のもとで検討されている．本研究では，より現実に近い真のパラメータが未知の仮定のもとで推薦システムの新規顧客問題における半教師付き学習方法を提案する．学習データは完全データと不完全データによって構成される．提案方法ではEMアルゴリズム（expectation-maximization algorithm）を用いる．数例のシミュレーションによって提案方法の有効性を示す．","subitem_description_type":"Abstract"},{"subitem_description":"Markov decision processes(MDP) are applied to a new customer problem of recommender system in previous research. In the previous research the true parameters of MDP are known. In this research we propose a semi-supervised learning method for the new customer problem of recommender system under the condition that the true parameters of MDP are unknown. Learning data consist of complete data and incomplete data. In the proposed method EM(expectation-maximization) algorithm is used. The effectiveness of the proposed method is shown by some simulations.","subitem_description_type":"Abstract"}]},"item_3_publisher_212":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"バイオメディカル・ファジィ・システム学会"}]},"item_3_rights_192":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"c 2018 Biomedical Fuzzy Systems Association"}]},"item_3_select_195":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_select_item":"publisher"}]},"item_3_source_id_187":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2424-2578","subitem_source_identifier_type":"PISSN"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"前田, 康成","creatorNameLang":"ja"}],"nameIdentifiers":[{},{}]},{"creatorNames":[{"creatorName":"山内, 翔","creatorNameLang":"ja"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 正清","creatorNameLang":"ja"}],"nameIdentifiers":[{},{}]},{"creatorNames":[{"creatorName":"松嶋, 敏泰","creatorNameLang":"ja"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"MAEDA, Yasunari","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yamauchi, Sho","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"SUZUKI, Masakiyo","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Matsushima, Toshiyasu","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-12-11"}],"displaytype":"detail","filename":"推薦システムの新規顧客問題における半教師付き学習.pdf","filesize":[{"value":"3.0 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"推薦システムの新規顧客問題における半教師付き学習","url":"https://kitami-it.repo.nii.ac.jp/record/8679/files/推薦システムの新規顧客問題における半教師付き学習.pdf"},"version_id":"a52eaa13-1c44-47c7-8e19-976c5417924c"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"推薦システム","subitem_subject_scheme":"Other"},{"subitem_subject":"マルコフ決定過程","subitem_subject_scheme":"Other"},{"subitem_subject":"新規顧客問題","subitem_subject_scheme":"Other"},{"subitem_subject":"半教師付き学習","subitem_subject_scheme":"Other"},{"subitem_subject":"recommender system","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"Markov decision processes","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"new customer problem","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"semi-supervised learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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":"推薦システムの新規顧客問題における半教師付き学習","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"推薦システムの新規顧客問題における半教師付き学習","subitem_title_language":"ja"},{"subitem_title":"Semi-supervised Learning for a New Customer Problem in Recommender System","subitem_title_language":"en"}]},"item_type_id":"3","owner":"1","path":["86"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2018-12-11"},"publish_date":"2018-12-11","publish_status":"0","recid":"8679","relation_version_is_last":true,"title":["推薦システムの新規顧客問題における半教師付き学習"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2022-12-13T02:22:12.753906+00:00"}