@article{ yamaba_serendipity-oriented_2013,
  series = {17th International Conference in Knowledge Based and Intelligent Information and Engineering Systems - {KES}2013},
  title = {On a Serendipity-oriented Recommender System based on Folksonomy and its Evaluation},
  volume = {22},
  issn = {1877-0509},
  url = {http://www.sciencedirect.com/science/article/pii/S1877050913008971},
  doi = {10.1016/j.procs.2013.09.104},
  abstract = {The present paper proposes a recommendation method that focuses not only on predictive accuracy but also serendipity. In many of the conventional recommendation methods, items are categorized according to their attributes (genre, author, etc.) by the recommender in advance, and recommendations are made using the categorization. In the present study, the impression of users regarding an item is adopted as its feature, and items are categorized according to this feature. Such impressions are derived using folksonomy. A recommender system based on the proposed method was developed in the Java language, and the effectiveness of the proposed method was verified through recommender experiments.},
  urldate = {2014-10-02TZ},
  journal = {Procedia Computer Science},
  author = {Yamaba, Hisaaki and Tanoue, Michihito and Takatsuka, Kayoko and Okazaki, Naonobu and Tomita, Shigeyuki},
  year = {2013},
  keywords = {Augmented Expected Mutual Information, Folksonomy, Recommender System, Serendipity, Tag},
  pages = {276--284}
}

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