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User interest analysis with hidden topic in news recommendation system
Proceedings - 2010 International Conference on Asian Language Processing, IALP 2010 Số , năm 2010 (Tập , trang 211-214)
DOI: 10.1109/IALP.2010.75
Tài liệu thuộc danh mục: Scopus
Conference Paper
English
Từ khóa: Content based filtering; Hidden topic; Information resource; News recommendation; Recommendation system; Recommendation systems; Research areas; User interests; User's interest analysis; Internet; Natural language processing systems; Recommender systems
Tóm tắt tiếng anh
To take advantage of the Internet - vast but complicated information resources, Recommendation systems help users find out information they need by providing them personalized suggestions. This research area is receiving more and more attention from researchers and used in some famous websites like EBay1, Amazon2, etc. In this paper, we proposed a Recommendation System for Vietnamese electronic newspaper which uses content-based filtering techniques associating with the attention of users shown in user's profile. These users'attentions are determined by inferring a set of common Hidden Topics from the documents which users preferred. Experimental results showed that approach is feasible with positive results and its capabilities for reality development. � 2010 IEEE.
