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Building a web‐snippet clustering system based on a mixed clustering method

Lin‐Chih Chen (Department of Information Management, National Dong Hwa University, Hualien, Taiwan)

Online Information Review

ISSN: 1468-4527

Article publication date: 9 August 2011

Abstract

Purpose

Web‐snippet clustering has recently attracted a lot of attention as a means to provide users with a succinct overview of relevant results compared with traditional search results. This paper seeks to research the building of a web‐snippet clustering system, based on a mixed clustering method.

Design/methodology/approach

This paper proposes a mixed clustering method to organise all returned snippets into a hierarchical tree. The method accomplishes two main tasks: one is to construct the cluster labels and the other is to build a hierarchical tree.

Findings

Five measures were used to measure the quality of clustering results. Based on the results of the experiments, it was concluded that the performance of the system is better than current commercial and academic systems.

Originality/value

A high performance system is presented, based on the clustering method. A divisive hierarchical clustering algorithm is also developed to organise all returned snippets into a hierarchical tree.

Keywords

Citation

Chen, L. (2011), "Building a web‐snippet clustering system based on a mixed clustering method", Online Information Review, Vol. 35 No. 4, pp. 611-635. https://doi.org/10.1108/14684521111161963

Publisher

:

Emerald Group Publishing Limited

Copyright © 2011, Emerald Group Publishing Limited