Yinxing Li

Work place: Province Research Institution of Regional Economy Beihua University, Jilin, PR. China

E-mail: fnyjjgl@126.com


Research Interests: Information Systems, Database Management System, Information Storage Systems, Multimedia Information System


Yingxing Li was born in Jilin, China in March., 1963. He got doctoral degree in school of biological and agricultural engineering, Jilin University, Chuang Chun, China in 2006. His research filed is focus on optimization of information system and management information system. 
He is a professor at Beihua University, Jilin, China. He also is the dean of Province Research Institution of Regional Economy.

Author Articles
A Genetic Programming Framework for Topic Discovery from Online Digital Library

By Yinxing Li Ning Li

DOI: https://doi.org/10.5815/ijitcs.2010.01.05, Pub. Date: 8 Nov. 2010

Various topic extraction techniques for digital libraries have been proposed over the past decade. Generally the topic extraction system requires a large number of features and complicated lexical analysis. While these features and analysis are effective to represent the statistical characteristics of the document, they didn't capture the high level semantics. In this paper, we present a new approach for topic extraction. Our approach combines user's click stream data with traditional lexical analysis. From our point of view, the user's click stream directly reflects human understanding of the high-level semantics in the document. Furthermore, a simple, yet effective, piece-wise linear model for topic evolution is proposed. We apply genetic algorithm to estimate the model and extract topics. Experiments on the set of US congress digital library documents demonstrate that our approach achieves better accuracy for the topic extraction than traditional methods.

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