| A New Generalized Similarity-Based Topic Distillation Algorithm |
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| 作者姓名： | ZHOU Hongfang DANG Xiaohui |
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| 作者单位： | [1]School of Computer Science and Engineering, Xi＇an University of Technology, Xi＇an 710048, Shaanxi, China [2]Xi＇an Branch, Shaanxi Telecom Company Limited, Xi＇an 710000, Shaanxi, China |
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| 基金项目： | Supported by the Shaanxi Provincial Educational Depar tment Special-Purpose Technology and Research of China （06JX229） |
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| 摘 要： | 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 concept-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.
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| 关 键 词： | 广义相似性 超文本感应主题搜索 网络 计算机技术 |
| 文章编号： | 1007-1202（2007）05-0789-04 |
| 收稿时间： | 6 February 2007 |
| 修稿时间： | 2007-02-06 |
A new generalized similarity-based topic distillation algorithm |
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| ZHOU Hongfang DANG Xiaohui.A New Generalized Similarity-Based Topic Distillation Algorithm[J].Wuhan University Journal of Natural Sciences,2007,12(5):789-792. |
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| Authors: | Zhou Hongfang Dang Xiaohui |
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| Institution: | (1) School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, 710048, Shaanxi, China;(2) Xi’an Branch, Shaanxi Telecom Company Limited, Xi’an, 710000, Shaanxi, China |
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| Abstract: | 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 concept-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.
Biography: ZHOU Hongfang(1976–), female, Lecturer, Ph.D., research direction: data mining and knowledge discovery in databases. |
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| Keywords: | generalized similarity hypertext induced topic search topic distillation topic drift |
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