An efficient algorithm for clustering search engine results

Hui Zhang; Bin Pang; Ke Xie; Hui Wu

doi:10.1109/ICCIAS.2006.295296

An efficient algorithm for clustering search engine results

Hui Zhang^*
, Bin Pang
, Ke Xie
, Hui Wu

^*Corresponding author for this work

School of Computer Science and Engineering

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

With the increasing number of Web documents in the Internet, the most popular keyword-matchingbased search engines, such as Google, often return a long list of search results ranked based on their relevancy and importance to the query. To cluster the search engine results can help users find the results in several clustered collections, so it is easy to locate the valuable search results that the users really needed. In this paper, we propose a new Key-Feature Clustering (KFC) algorithm which firstly extracts the significant keywords from the results as key features and cluster them, then clusters the documents based on these clustered key features. At last, the paper presents and analyzes the results from experiments we conducted to test and validate the algorithm.

Original language	English
Title of host publication	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Publisher	IEEE Computer Society
Pages	1429-1434
Number of pages	6
ISBN (Print)	1424406056, 9781424406050
DOIs	https://doi.org/10.1109/ICCIAS.2006.295296
State	Published - 2006
Event	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 - Guangzhou, China Duration: 3 Oct 2006 → 6 Oct 2006

Publication series

Name	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Volume	2

Conference

Conference	2006 International Conference on Computational Intelligence and Security, ICCIAS 2006
Country/Territory	China
City	Guangzhou
Period	3/10/06 → 6/10/06

Access to Document

10.1109/ICCIAS.2006.295296

Cite this

Zhang, H., Pang, B., Xie, K., & Wu, H. (2006). An efficient algorithm for clustering search engine results. In 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 (pp. 1429-1434). Article 4076202 (2006 International Conference on Computational Intelligence and Security, ICCIAS 2006; Vol. 2). IEEE Computer Society. https://doi.org/10.1109/ICCIAS.2006.295296

@inproceedings{0c18acdde7624a92998f77c7646d7f6e,

title = "An efficient algorithm for clustering search engine results",

abstract = "With the increasing number of Web documents in the Internet, the most popular keyword-matchingbased search engines, such as Google, often return a long list of search results ranked based on their relevancy and importance to the query. To cluster the search engine results can help users find the results in several clustered collections, so it is easy to locate the valuable search results that the users really needed. In this paper, we propose a new Key-Feature Clustering (KFC) algorithm which firstly extracts the significant keywords from the results as key features and cluster them, then clusters the documents based on these clustered key features. At last, the paper presents and analyzes the results from experiments we conducted to test and validate the algorithm.",

author = "Hui Zhang and Bin Pang and Ke Xie and Hui Wu",

year = "2006",

doi = "10.1109/ICCIAS.2006.295296",

language = "英语",

isbn = "1424406056",

series = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006",

publisher = "IEEE Computer Society",

pages = "1429--1434",

booktitle = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006",

address = "美国",

note = "2006 International Conference on Computational Intelligence and Security, ICCIAS 2006 ; Conference date: 03-10-2006 Through 06-10-2006",

}

Zhang, H, Pang, B, Xie, K & Wu, H 2006, An efficient algorithm for clustering search engine results. in 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006., 4076202, 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006, vol. 2, IEEE Computer Society, pp. 1429-1434, 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006, Guangzhou, China, 3/10/06. https://doi.org/10.1109/ICCIAS.2006.295296

An efficient algorithm for clustering search engine results. / Zhang, Hui; Pang, Bin; Xie, Ke et al.
2006 International Conference on Computational Intelligence and Security, ICCIAS 2006. IEEE Computer Society, 2006. p. 1429-1434 4076202 (2006 International Conference on Computational Intelligence and Security, ICCIAS 2006; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Pang, Bin

AU - Xie, Ke

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AB - With the increasing number of Web documents in the Internet, the most popular keyword-matchingbased search engines, such as Google, often return a long list of search results ranked based on their relevancy and importance to the query. To cluster the search engine results can help users find the results in several clustered collections, so it is easy to locate the valuable search results that the users really needed. In this paper, we propose a new Key-Feature Clustering (KFC) algorithm which firstly extracts the significant keywords from the results as key features and cluster them, then clusters the documents based on these clustered key features. At last, the paper presents and analyzes the results from experiments we conducted to test and validate the algorithm.

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M3 - 会议稿件

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BT - 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

PB - IEEE Computer Society

T2 - 2006 International Conference on Computational Intelligence and Security, ICCIAS 2006

Y2 - 3 October 2006 through 6 October 2006

ER -

An efficient algorithm for clustering search engine results

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