Top-N Books Recommendation using Wikipedia
نویسندگان
چکیده
This paper presents an approach of recommending a ranked list of books to a user. A user profile is defined by a few liked and disliked books. To recommend a book, we calculate semantic relatedness of the given book to the liked and disliked books by using Wikipedia. Based on the obtained scores, we predict ratings of the book. We evaluate our approach on a dataset that consists of 6,181 users, 8,171 books and 67,990 user-item pairs to predict the rating.
منابع مشابه
The Lowlands team at TRECVID 2007
Type Run Description MAP Official A UTen English ASR 0.0031 A UTt hs-t2-nm Top-2 concepts from t hs graph method with neighbor multiply 0.0137 A UTwiki-t2-nm Top-2 Wikipedia concepts with neighbor multiply 0.0131 A UTwiki-t2-en-nm Top-2 Wikipedia concepts and English ASR with neighbor multiply 0.0107 A UTwiki-t2-nl-nm Top-2 Wikipedia concepts and Dutch ASR with neighbor multiply 0.0096 A UTword...
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تاریخ انتشار 2015