Clustering Method Based on Label Hierarchical Search Results

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Clustering Method Based on Label Hierarchical Search Results

更新时间：2025-07-09

- Clustering Method Based on Label Hierarchical Search Results
- Vol. 43, Issue 4, Pages: 18-21+38(2009)
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Online First：10 April 2009，
  
  Published：2009
- 稿件说明：
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Clustering Method Based on Label Hierarchical Search Results[J]. 2009, 43(4): 18-21+38.
DOI：

Clustering Method Based on Label Hierarchical Search Results[J]. 2009, 43(4): 18-21+38. DOI：

摘要

为了提高搜索引擎返回结果的可浏览性

满足用户对查询质量的要求

提出了一种层次化搜索结果聚类方法.首先

从搜索引擎的返回结果提取出文档集

并对每一个文档进行词干化、去除停用词等操作.然后

根据词共现信息来发现文档集中的频繁2元组

再将2元组扩展为n元组

对所有元组进行去冗余、重要性排序

从而获得候选聚类标签.最后

基于该标签对返回结果中的文档进行分配与聚集

形成层次化聚类结果.实验结果表明

所提方法可以通过获得的准确、可读性较好的聚类标签

帮助用户有效地浏览搜索引擎返回的结果.与Vivisimo、STC、Lingo算法比较

以及在多个评价指标上的综合实验结果也表明

该方法是有效的.

Abstract

A novel clustering method based on hierarchical search results is proposed to facilitate users browsing web search results produced by search engines and to locate the interesting information quickly and efficiently. The snippets are collected and preprocessed. Frequent bigrams are identified based on term co-occurrence information

from which n-grams are obtained. After filtering out the redundant phrases and sorting by significance

candidate cluster labels are obtained. Finally

the snippets are grouped into clusters based on the candidate cluster labels

and a hierarchical result is generated. Experimental results show that the proposed method can generate accurate and highly readable cluster labels

which can help users effectively browse through the search results returned by search engine

and locating their interesting information. The method outperforms Vivisimo

Lingo and STC algorithms on different indexes. A comparison on Chinese dataset further illustrates the validity of the method.

关键词

Keywords

references

SMADJA F. Retrieving collocations from text: Xtract[J]. Computational Linguistics, 1993, 19(1): 143-177.

ZHANG Dell, DONG Yisheng. Semantic hierarchical, online clustering of Web search results [C]∥Proceeding of the 6th Asia Pacific Web Conference(APWEB). Berlin, Germany: Springer-Verlag, 2004:69-78.

ZAMIR O, ETZIONI O. Grouper: a dynamic clustering interface to Web search results [C]∥Proceedings of the 8th International World Wide Web Conference.Toronto, Canada: Elsevier,1999:283-296.

OSINSKI S. An algorithm for clustering of Web search results [D]. Poznan,Poland: Poznan University of Technology, 2003.

ZENG Huajun, HE Qicai, CHEN Zheng, et al. Learning to cluster Web search results [C]∥Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. New York, USA: ACM, 2004: 210-217.

张云, 冯博琴, 麻首强,等. 蚁群-遗传融合的文本聚类算法 [J]. 西安交通大学学报,2007, 41(10): 1146-1150.

ZHANG Yun, FENG Boqin, MA Shouqiang, et al. Text clustering based on fusion of ant colony algorithm and genetic algorithm [J]. Journal of Xi'an Jiaotong University, 2007, 41(10): 1146-1150.

GERACI F, PELLEGRINI M, MAGGINI M, et al. Cluster generation and cluster labeling for Web snippets: a fast and accurate hierarchical solution [J]. Internet Mathematics, 2007, 3(4):413-444.

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