@article{oai:nagoya.repo.nii.ac.jp:00018756,
 author = {吉川, 大弘 and Yoshikawa, Tomohiro and 森, 貴章 and Mori, Takafumi and 古橋, 武 and Furuhashi, Takeshi},
 issue = {1},
 journal = {情報処理学会論文誌: 数理モデル化と応用},
 month = {Mar},
 note = {近年,インターネットの普及とそれにともなう各種メディアの発達により,ユーザがアクセス可能な情報の量は膨大なものとなったが,一方で,ユーザにとって価値のある情報を選択することは困難となっている.そのため,ユーザのアイテム選択を支援する"レコメンデーション"に注目が集まり,様々な推薦システムが実用化され始めている.このような推薦システムの評価には,これまで主に"精度"が用いられてきたが,近年,ユーザ満足度の観点から,他にも様々な側面を評価する必要性が指摘され始めている."Serendipity"はその中の1つであり,推薦アイテムの目新しさ,意外性を表す.本論文では,Serendipityの一面として"Personalizability"を定義し,Personalizabilityを考慮した推薦手法を提案する.また,提案手法をベンチマークデータに適用し,推薦における精度とPersonalizabilityのバランスが調節可能であること,従来手法と比べ,Personalizabilityにおいて優れていることを示す., Recently, a user can access a huge amount of information with the popularization of Internet and the development of media associated with that. On the other hand, it becomes difficult for him/her to choose desirable or valuable ones. Then various recommendation systems have been studied and put into practical use to support users' selection. Though "accuracy" has been used as the evaluation of these systems so far, it is said that other evaluation factors are also needed from the aspect of the satisfaction of users. "Serendipity," which includes novelty or unexpectedness, is one of the evaluation indexes for user satisfaction. This paper defines and quantifies "Personalizability" as a part of "Serendipity." This paper proposes a recommendation system considering "Personalizability," and applies the proposed method to benchmark data. It shows that this method can adjust the balance between "Accuracy" and "Personalizability" and it is superior to the conventional method in terms of "Personalizability."},
 pages = {111--118},
 title = {Personalizabilityを考慮した推薦システムの提案},
 volume = {6},
 year = {2013}
}