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The procedure of hypertext induced topic search based on a semantic relation model is analyzed,and the reason for the topic drift of HITS algorithm was found to prove that Web pages are projected to a wrong latent semantic basis. A new con-cept-generalized similarity is introduced and,based on this,a new topic distillation algorithm GSTDA(generalized similarity based topic distillation algorithm) was presented to improve the quality of topic distillation. GSTDA was applied not only to avoid the topic drift,but also to explore relative topics to user query. The experimental results on 10 queries show that GSTDA reduces topic drift rate by 10% to 58% compared to that of HITS(hypertext induced topic search) algorithm,and discovers several relative topics to queries that have multiple meanings.
The procedure of hypertext induced topic search based on a semantic relation model is analyzed, and the reason for the topic drift of HITS algorithm was found to prove that Web pages are projected to a wrong latent semantic basis. A new con-cept-generalized similarity is introduced and, based on this, a new topic distillation algorithm GSTDA (generalized similarity based topic topic distillation algorithm) was presented to improve the quality of topic distillation. GSTDA was applied not only to avoid the topic drift, but also to explore relative topics to user query. The experimental results on 10 queries show that GSTDA reduces topic drift rate by 10% to 58% compared to that of HITS (hypertext induced topic search) algorithm, and discovers several relative topics to queries that have multiple meanings.