Algorithm for Topic Distillation and Hierarchical Exploration Based on New Fuzzy Set
Boqin Feng · Jisuanji gongcheng · 2007
To interpret the procedure of hypertext induced topic search based on a semantic relation model,the reason about the topic drift of HITS is found that Web pages are projected to a wrong latent semantic basis.A new fuzzy set based algorithm for topic distillation and hierarchical exploration(FSTH)is presented to improve the quality of topic distillation.Personalized root set and base set with query expansion is constructed using individual query logs to avoid the topic drift,and applying a hierarchical division algorithm based on fuzzy set to explore relative topics of user query,and then using HITS to evaluate and return authority pages of relative topics to end-users.The experimental results on 10 queries show that FSTH reduces topic drift rate by 7% to 53% compared to that of HITS,and discovers several relative topics to queries that have multiple meanings.