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http://dx.doi.org/10.9717/kmms.2011.14.11.1467

A Design of HPPS(Hybrid Preference Prediction System) for Customer-Tailored Service  

Jeong, Eun-Hee (강원대학교 지역경제학과)
Lee, Byung-Kwan (관동대학교 컴퓨터학과)
Publication Information
Journal of Korea Multimedia Society / v.14, no.11, 2011 , pp. 1467-1477 More about this Journal
Abstract
This paper proposes a HPPS(Hybrid Preference Prediction System) design using the analysis of user profile and of the similarity among users precisely to predict the preference for custom-tailored service. Contrary to the existing NBCFA(Neighborhood Based Collaborative Filtering Algorithm), this paper is designed using these following rules. First, if there is no neighbor's commodity rating value in a preference prediction formula, this formula uses the rating average value for a commodity. Second, this formula reflects the weighting value through the analysis of a user's characteristics. Finally, when the nearest neighbor is selected, we consider the similarity, the commodity rating, and the rating frequency. Therefore, the first and second preference prediction formula made HPPS improve the precision by 97.24%, and the nearest neighbor selection method made HPPS improve the precision by 75%, compared with the existing NBCFA.
Keywords
HPPS; Customer-Tailored Service; Nearest Neighbor Selection; Similarity; Weight;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
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