Journal Published Online: 19 August 2022
Volume 51, Issue 3

Fast Retrieval Method of Massive Library Literature Resources Based on an Online Hash Algorithm



Aiming at the relatively large amount of library literature resources, a fast retrieval method for massive library literature resources based on an online hash algorithm is designed. The Pearson correlation coefficient is used to calculate the correlation between library literature resources, the collaborative filtering algorithm is used to realize the library literature resource mining based on the calculation results, and the least squares method is used to filter the nonsignificant data features in the mining results. Construct a Hash-B-tree to search the user’s library literature resources on a certain day, design a hash function lookup table to manage inactive metadata, and use fuzzy theory to simulate data with similar characteristics in the data divergence measurement sample, minimize the divergence of the sample data, and finally visualize the retrieval results based on the subject hierarchical relationship. The experimental results show that this method has the advantages of higher retrieval result accuracy, faster retrieval efficiency, and higher comprehensiveness of retrieval results.

Author Information

Wang, Huan
Library, Harbin University of Science and Technology, Harbin, Heilongjiang, China
Pages: 12
Price: $25.00
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Stock #: JTE20220101
ISSN: 0090-3973
DOI: 10.1520/JTE20220101