Research on Automatic Classification Model of Massive Academic Resources in Library

• Main Authors: yangya, yiyuanhong
• Format: Article
• Language: zho
• Published: LIS Press 2018-06-01
• Series: Zhishi guanli luntan
• Subjects: automatic classification
• Online Access: http://kmf.ac.cn/p/137/

[Purpose/significance] In order to solve the problem that users often have difficulty in obtaining information in massive digital resources of library, this paper construct a personalized knowledge service system, which is the inevitable choice of library to help users to get rid of the information overload predicament and improve the quality of knowledge service. [Method/process] Firstly, this paper built a mapping model of Chinese Library Classification(CLC) and subject classification. Then, based on Hadoop distributed processing platform, it proposed to build automatic classification model of massive academic resources in libraries by improving TF-IDF+ Bayesian algorithm, the model can help to construct the personalized knowledge service systems in library. [Result/conclusion]In the experimental part，we collected more than 6 million documents from CNKI as the original training corpus (corpus covers 75 disciplines) to test the effectiveness of the classification model, the experimental result shows that the classification efficiency and effectiveness of the model are achieved.