{"updated":"2025-01-19T15:04:14.851075+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00209007","sets":["581:10433:10434"]},"path":["10434"],"owner":"44499","recid":"209007","title":["ケアプラン作成支援システムのための非負値行列因子分解に基づく特徴語補完"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-01-15"},"_buckets":{"deposit":"b389d93d-ea67-4629-aee0-867ac15321fd"},"_deposit":{"id":"209007","pid":{"type":"depid","value":"209007","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ケアプラン作成支援システムのための非負値行列因子分解に基づく特徴語補完","author_link":["525828","525830","525829","525827"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ケアプラン作成支援システムのための非負値行列因子分解に基づく特徴語補完"},{"subitem_title":"Terms Completion based on Nonnegative Matrix Factorization for Care Planning Support System","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[一般論文（推薦論文, 特選論文）] 協調フィルタリング，クエリ拡張，非負値行列因子分解，推薦システム，ケアマネジメント","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2021-01-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"横浜国立大学大学院理工学府"},{"subitem_text_value":"横浜国立大学大学院理工学府"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Engineering Science, Yokohama National University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Engineering Science, Yokohama National University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/209007/files/IPSJ-JNL6201044.pdf","label":"IPSJ-JNL6201044.pdf"},"date":[{"dateType":"Available","dateValue":"2023-01-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL6201044.pdf","filesize":[{"value":"1.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"190a80ef-abe6-414e-8d1c-c0c15831775e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"兵頭, 幸起"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"濱上, 知樹"}],"nameIdentifiers":[{}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Koki, Hyodo","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tomoki, Hamagami","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"超高齢化と労働人口減が進む日本において，機械学習による介護分野の支援に期待が高まっている．本研究では，過去の介護記録を基に，利用者に適したケアプラン文書をメモリベース協調フィルタリングを用いて推薦する「ケアプラン作成支援システム」の実現を目指す．メモリベース協調フィルタリングでは文書構造を保持した推薦が期待される．しかし，訓練データ間，単語間の関係が考慮されないことやスパース性の高い文書行列に対して適用困難であることが課題となる．そこで，メモリベース協調フィルタリングを用いる前処理として，ケアプラン文書に対して非負値行列因子分解（NMF）に基づくクエリ拡張を行う推薦手法を提案する．実験では，実際のケアマネジメントデータを用いた推薦を行うことで提案手法による推薦性能改善を確認した．また，補完される特徴語の性質を考察することにより，提案手法は，上位の推薦精度を維持した上で下位の推薦精度の向上を達成可能であることを明らかにした．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In Japan's rapidly aging society, there are high expectations for machine learning to support the nursing care sector. This study aims to develop a “care planning support system” that recommends care plan documents based on past care records using memory-based collaborative filtering. This method is expected to recommend keeping the document structure. However, it is a issue that relationships between training data and between words are not taken into consideration, and it is difficult to apply matrices with high sparsity. In consideration of these problems, we perform query expansion based on nonnegative matrix factorization for care plan documents as preprocessing to apply memory-based collaborative filtering. In the experiments, we confirmed the performance improvement by the proposed method using the real care management data. In addition, we examined complementary feature words and clarified their properties.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"377","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"369","bibliographicIssueDates":{"bibliographicIssueDate":"2021-01-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"62"}]},"relation_version_is_last":true,"item_2_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.20729/00208905","subitem_identifier_reg_type":"JaLC"}]},"weko_creator_id":"44499"},"created":"2025-01-19T01:10:20.927711+00:00","id":209007,"links":{}}