Classification and Retrieval Method of Library Book Information Based on Data Mining

The current classified retrieval of book information is mainly based on the key words of books. When there are interdisciplinary contents in books, it is easy to ignore the correlation between book information, resulting in a sharp decline in the retrieval accuracy. In order to improve the quality of library information retrieval service, aiming at the problems of the above traditional classification retrieval methods, this paper studies the library book information classification retrieval method based on data mining. After preprocessing the book information, the Apriori algorithm of data mining is used to mine the deep management of information, and the decision tree algorithm is used to determine the classification of information. Using the concepts in book information, this paper constructs the concept map of book information and builds the information retrieval framework. Use Markov network model to realize book information classification and retrieval. In the test, the retrieval accuracy of the proposed retrieval methods is higher than 92%, and the retrieval performance is significantly improved. Through the research and application of this method, the transformation from the traditional library service concept to the personalized information service concept is promoted.