✦ LIBER ✦

Refining web search engine results using incremental clustering

✍ Scribed by Ya-Jun Zhang; Zhi-Qiang Liu

Publisher: John Wiley and Sons
Year: 2004
Tongue: English
Weight: 141 KB
Volume: 19
Category: Article
ISSN: 0884-8173
DOI: 10.1002/int.10161

No coin nor oath required. For personal study only.

✦ Synopsis

In this article, we present a new solution to improve the Web search performance. Our algorithm is based on a new clustering algorithm that classifies the results of a query from a search engine into subgroups and assigns each group a short series of keywords together with some statistics data. Then, the user may look into the group with the keywords that he/she finds interesting. Compared with the approaches available in the literature, our algorithm does not require the number of groups as the prior knowledge; it starts from a single prototype group and adaptively expands the prototype set based on a self-spawning splitting scheme until all the groups are finally identified.

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