{"created":"2025-01-19T00:44:51.962525+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00174754","sets":["934:6391:8667:8884"]},"path":["8884"],"owner":"11","recid":"174754","title":["ホームネットワーク内接続機器の情報を活用した世帯人数推定システム"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-09-22"},"_buckets":{"deposit":"179e7c37-bb78-474a-bdad-e56c16db8919"},"_deposit":{"id":"174754","pid":{"type":"depid","value":"174754","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"ホームネットワーク内接続機器の情報を活用した世帯人数推定システム","author_link":["360932","360931","360934","360933","360936","360935"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ホームネットワーク内接続機器の情報を活用した世帯人数推定システム"},{"subitem_title":"A System That Estimates a Household Size Using Information from Devices Connected to Home Network","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[コンシューマ・デバイス論文] ホームネットワーク，機械学習，情報家電，ネットワークプロトコル","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2016-09-22","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"日本電信電話株式会社NTTサービスエボリューション研究所"},{"subitem_text_value":"日本電信電話株式会社NTTサービスエボリューション研究所"},{"subitem_text_value":"日本電信電話株式会社NTTサービスイノベーション総合研究所"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NTT Service Evolution Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NTT Service Evolution Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NTT Service Innovation Laboratory Group","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/174754/files/IPSJ-TCDS0602003.pdf","label":"IPSJ-TCDS0602003.pdf"},"date":[{"dateType":"Available","dateValue":"2018-09-22"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TCDS0602003.pdf","filesize":[{"value":"1.6 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":"820e57ab-7e4d-4a06-9379-6756a9318ede","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"美原, 義行"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山口, 徹也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"高倉, 健"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yoshiyuki, Mihara","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tetsuya, Yamaguchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takeshi, Takakura","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628043","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_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2186-5728","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本論文では，ホームネットワークに接続された機器の情報を活用して，機器を所有している世帯の人数を推定するシステムについて述べる．機器から取得可能な情報とは，機器の種別やメーカ名等の機器名情報と，各機器の利用状態を記録した利用情報のことである．本システムでは，膨大な利用情報に対して，世帯の特徴を表現できるよう丸め処理を実施し，学習して推定モデルを作成することで世帯人数を推定する．世帯人数を把握できることにより，レコメンドに向けある商品やサービスに適した世帯を抽出することができ，また，世帯ごとの活動を測定するマーケティングにも応用することが可能となる．本システムを実ホームネットワークに適用し，各ホームネットワークから機器名情報と利用情報を収集でき，これらの情報から世帯人数推定のモデルを構築できることを確認した．本システムによる世帯人数推定の精度評価として，1,000世帯からアンケートにより機器名情報と利用情報，世帯人数情報を収集し，世帯人数の推定を実施した．その結果，ある特定の目的変数とそれ以外の目的変数のどちらに適合するかを判定する二値分類にて平均83.7%の精度で推定できた．そして，商品やサービスのレコメンドに適した世帯である，可処分所得が多い1人世帯においては89.5%の適合率で推定でき，子どもを含む世帯が多い3人以上世帯においては88.3%の適合率で推定できた．機器に関する情報から，高い精度で世帯の人数を推定でき，世帯人数推定における機器に関する情報の有効性を確認することができた．","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In this article, we propose a system that estimates household size from the information held by devices connected to the home network. This information includes device name information, such as device type or manufacturer name, and usage status information of each device. This system agglomerates the vast amount of usage status information in order to estimate the feature of each family. This system estimates the household size by learning device information and by making a learning model. Estimating the household size allows us to provide services that more appropriate to the family, or sell the information to other marketing services. We verify that the system collects device name information and usage status information from actual home network and makes the learning model. We submit questionnaires to 1,000 families to gather household size, device names, and the usage status information and then process the data to extract household size. Our system estimates the household size with 83.7% precision for binary classification. 89.5% precision for one-person household, which has a lot of disposal income and is appropriate for recommendation of service or products. 88.3% precision for more than three household, in which there are many families with children. Clearly the proposed system can estimate household size with a high degree of accuracy. The results show the effectiveness of using device information to estimate the household size. Moreover, we verify that using agglomerated usage status yields higher accuracy than if it is not used. We can the effectiveness of round usage status information.","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"22","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌コンシューマ・デバイス＆システム（CDS）"}],"bibliographicPageStart":"14","bibliographicIssueDates":{"bibliographicIssueDate":"2016-09-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"6"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":174754,"updated":"2025-01-20T06:35:24.305124+00:00","links":{}}