Co-occurrence Word Retrieval Based on the Lexical Attraction and Repulsion Model
Shengrui Li · Zhongwen xinxi xuebao · 2004
Co-occurrence word retrieval is very important in information mining and natural language processing. But traditional co-occurrence word retrieval methods used only a single statistic method, so the result is very imprecise, and needs lots of manual collation. In this paper we present a co-occurrence words extraction algorithm based on the lexical attraction and repulsion model, and combine some common statistical methods with the algorithm to improve its effect. In the open test, our system's Interesting performance is 60.87%. We show good performance in speed and precision when applied the algorithm on a co-occurrence search system based on web.