{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00231722","sets":["1164:6390:11456:11457"]},"path":["11457"],"owner":"44499","recid":"231722","title":["小売店におけるID-POSデータを用いた顧客情報の推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-01-15"},"_buckets":{"deposit":"c0d78463-3340-4c3f-ba72-69bdf0510706"},"_deposit":{"id":"231722","pid":{"type":"depid","value":"231722","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"小売店におけるID-POSデータを用いた顧客情報の推定","author_link":["626052","626055","626058","626056","626057","626054","626053"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"小売店におけるID-POSデータを用いた顧客情報の推定"},{"subitem_title":"Estimation of Customer Information Using ID-POS Data in Retail Stores","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"情報伝達","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-01-15","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"和歌山大学大学院システム工学研究科"},{"subitem_text_value":"和歌山大学システム工学部"},{"subitem_text_value":"株式会社オークワ"},{"subitem_text_value":"株式会社オークワ"},{"subitem_text_value":"株式会社オークワ"},{"subitem_text_value":"株式会社オークワ"},{"subitem_text_value":"株式会社オークワ"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Systems Engineering, Wakayama University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Systems Engineering, Wakayama University","subitem_text_language":"en"},{"subitem_text_value":"Okuwa Co., Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Okuwa Co., Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Okuwa Co., Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Okuwa Co., Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Okuwa Co., Ltd.","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/231722/files/IPSJ-CDS24039011.pdf","label":"IPSJ-CDS24039011.pdf"},"date":[{"dateType":"Available","dateValue":"2026-01-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CDS24039011.pdf","filesize":[{"value":"7.7 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":"47"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"c565fd09-6439-44fc-9cd6-b78a8256c677","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"井口, 拓己"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"吉野, 孝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"貴志, 祥江"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田井, 紗瑛子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"坂本, 明一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"宮崎, 裕之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大西, 剛"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628327","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_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8604","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年,スーパーマーケットにおけるポイントカードの導入が増加しており,様々な小売店が独自のポイントカードを導入している.小売店がポイントカードを導入することにより,性別や年齢などの顧客情報を,レシートの情報と紐付けて収集することが可能であり,このようなデータのことを ID-POS データと呼ぶ.ID-POS データを収集し,分析することで,マーケティング戦略への応用が期待される.しかし,ID-POS データの中には,顧客情報がわからない非会員と分類される顧客が一定数存在するため,顧客情報が欠損したデータが存在し,十分に活用できていないといった問題がある.そこで本研究では,ID-POS データの価値をさらに向上させるため,会員顧客のデータを利用して,顧客の性別や年齢の情報を推定することを目的とした分析を機械学習モデルを用いて行った.分析の結果,ランダムフォレストとニューラルネットワークが他の機械学習モデルと比較して高い精度を示し,性別が 58~75%,年齢が 49~54% であり,ある程度推定が可能であった.また,男女や各年齢層の分布に着目した分析では,会員顧客と非会員顧客で購買のパターンや客層に違いが生じることを明らかにした.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告コンシューマ・デバイス&システム(CDS)"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-01-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"11","bibliographicVolumeNumber":"2024-CDS-39"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":231722,"updated":"2025-01-19T10:39:22.664900+00:00","links":{},"created":"2025-01-19T01:32:11.556299+00:00"}