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Next Generation Search Engine for the Result Clustering Technology

Next Generation Search Engine for the Result Clustering Technology
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Author(s): Lin-Chih Chen (National Dong Hwa University, Taiwan)
Copyright: 2012
Pages: 17
Source title: Next Generation Search Engines: Advanced Models for Information Retrieval
Source Author(s)/Editor(s): Christophe Jouis (Universite Paris III, France and LIP6-Universite Pierre et Marie Curie, France), Ismail Biskri (Universite du Quebec A Trois Rivieres, Canada), Jean-Gabriel Ganascia (LIP6 and CNRS-Universite Pierre et Marie Curie, France)and Magali Roux (LIP6 and CNRS-Universite Pierre et Marie Curie, France)
DOI: 10.4018/978-1-4666-0330-1.ch012

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Abstract

Result clustering has recently attracted a lot of attention to provide the users with a succinct overview of relevant search results than traditional search engines. This chapter proposes a mixed clustering method to organize all returned search results into a hierarchical tree structure. The clustering method accomplishes two main tasks, one is label construction and the other is tree building. This chapter uses precision to measure the quality of clustering results. According to the results of experiments, the author preliminarily concluded that the performance of the system is better than many other well-known commercial and academic systems. This chapter makes several contributions. First, it presents a high performance system based on the clustering method. Second, it develops a divisive hierarchical clustering algorithm to organize all returned snippets into hierarchical tree structure. Third, it performs a wide range of experimental analyses to show that almost all commercial systems are significantly better than most current academic systems.

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