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Use of Library Loan Records for Book Recommendation

Keita Tsuji, Erika Kuroo, Sho Sato, Ui Ikeuchi, Atsushi Ikeuchi, Fuyuki Yoshikane, Hiroshi Itsumura


To show the effectiveness or limitation of using library loan records for book recommendation, we implemented the collaborative filtering system (henceforth LLR system) which is similar to that of Harada & Masuda (2010) and compared its performance with Amazon. It was found that LLR system could not outperform Amazon. Library loan records contain users' privacy and collaborative filtering usually requires much computer resources. We should pay attention to whether LLR system is really effective enough to worth its cost


Library loan records, Book recommendation, Collaborative filtering, Amazon, privacy

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