Abstract
Today there are a lot of recommender systems operating on the web. These systems use content-based filtering or collaborative filtering or hybrid approach that was studied before. These techniques operate recommendation by using features of user and item, similarity of users, and items. Even though there is a consideration of attributes of items and users, but there is not much consideration of the quality of items. This is why item quality is not easy to be measured. This paper computes item quality, suggests it to apply to the recommender system, and presents it by analyzing the influence.
This research was financially supported by the Ministry of Commerce, Industry and Energy(MOCIE) and Korea Industrial Technology Foundation(KOTEF) through the Human Resource Training Project for Regional Innovation.
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Cho, Sh., Lee, Mh., Kim, BH., Choi, Ei. (2008). A Recommendation Using Item Quality. In: Nguyen, N.T., Jo, G.S., Howlett, R.J., Jain, L.C. (eds) Agent and Multi-Agent Systems: Technologies and Applications. KES-AMSTA 2008. Lecture Notes in Computer Science(), vol 4953. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78582-8_89
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DOI: https://doi.org/10.1007/978-3-540-78582-8_89
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78581-1
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