Abstract: In order to overcome the problems of inaccurate recommendation results and high response delay existing in traditional recommendation methods, this paper proposes an interest reading recommendation method based on big data technology for intelligent library. Build the recommendation platform of intelligent library, design the cataloging subsystem, book category setting subsystem, new book storage subsystem and new journal storage subsystem. Through big data processing technology, users’ reading interest in each subsystem is clustered and fully mined. Based on the results of reading interest mining, the user interest model is established according to the semantic topic and the updating scheme of user interest model is designed. Combined with the user’s score, we recommend the reading target which accords with the user’s reading interest to the user. The experimental results show that compared with the traditional recommendation method, the proposed method can achieve high-precision reading recommendation with low response delay, and the minimum delay is only 0.019.
Keywords: Big data technology, intelligent library, interest reading recommendation, data mining