Based Collaborative Filtering Personalized Book Recommendations System Design And Implementation

In recent years, with the continuous construction and development of university library, the number of books in libraries also increased year by year, how to found interested in books from the massive books is a concerned problems by every reader. Book personalized recommendation technology can solve this problem.Personalized recommendation technology is a popular intelligent technology in recent years, it has been successfully used in the electronic commerce, search engine platform. This technology is a product that meets the user preferences by using massive user information data, analysis, and through a series of mining algorithm. Personalized recommendation system is a set of comprehensive information system based on Personalized Recommendation Algorithm, the system can recommend the real-time results to the user, the user can feedback to the system according to the recommended results. Recommend systems can use these feedback to adjust the results, so that it is closer to the user's preferences.In this article, the collaborative filtering recommendation algorithm based on clustering and book category preference realized in the basis of the collaborative filtering and the classification of books in the library. Firstly, according to the number of days to borrowed books, the algorithm constructs the user's score to fill the scoring matrix. Then, the matrix uses the clustering method to pre process the preference of different book categories according to the user's preference. The processed results are input to the collaborative filtering algorithm, which is used to find the target user's neighbors in a number of clustering methods. At last, the target books are predicted by using the user's score in the user's neighbor set, and the output the book of higher score. This algorithm makes up for the data sparsity and scalability problems of traditional collaborative filtering algorithm in a certain extent.On the basis of the above algorithm, this article verifies the rationality and reliability of the algorithm, and develops a set of practical personalized book recommendation system. It is verified the accuracy of the proposed algorithm by the operation of the real system, and the collection of feedback results evaluated.