An efficient algorithm for clustering search engine results

Hui Zhang; Bin Pang; Ke Xie; Hui Wu

doi:10.1007/978-3-540-74377-4_69

An efficient algorithm for clustering search engine results

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

^*此作品的通讯作者

计算机学院

Beihang University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

2 引用（Scopus）

摘要

With the increasing number of Web documents in the Internet, the most popular keyword-matching-based 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.

源语言	英语
主期刊名	Computational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers
出版商	Springer Verlag
页	661-671
页数	11
ISBN（印刷版）	9783540743767
DOI	https://doi.org/10.1007/978-3-540-74377-4_69
出版状态	已出版 - 2007
活动	International Conference on Computational Intelligence and Security, CIS 2006 - Guangzhou, 中国期限: 3 11月 2006 → 6 11月 2006

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	4456 LNAI
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

会议

会议	International Conference on Computational Intelligence and Security, CIS 2006
国家/地区	中国
市	Guangzhou
时期	3/11/06 → 6/11/06

访问文件

10.1007/978-3-540-74377-4_69

其它文件与链接

链接到 Scopus 的出版物

引用此

Zhang, H., Pang, B., Xie, K., & Wu, H. (2007). An efficient algorithm for clustering search engine results. 在 Computational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers (页码 661-671). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 4456 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-540-74377-4_69

Zhang, Hui ; Pang, Bin ; Xie, Ke 等. / An efficient algorithm for clustering search engine results. Computational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers. Springer Verlag, 2007. 页码 661-671 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{a92886bb3c9f485cac5a8a2f465aa485,

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

abstract = "With the increasing number of Web documents in the Internet, the most popular keyword-matching-based 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 = "2007",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Computational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers",

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note = "International Conference on Computational Intelligence and Security, CIS 2006 ; Conference date: 03-11-2006 Through 06-11-2006",

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Zhang, H, Pang, B, Xie, K & Wu, H 2007, An efficient algorithm for clustering search engine results. 在 Computational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 4456 LNAI, Springer Verlag, 页码 661-671, International Conference on Computational Intelligence and Security, CIS 2006, Guangzhou, 中国, 3/11/06. https://doi.org/10.1007/978-3-540-74377-4_69

An efficient algorithm for clustering search engine results. / Zhang, Hui; Pang, Bin; Xie, Ke 等.
Computational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers. Springer Verlag, 2007. 页码 661-671 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 4456 LNAI).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - An efficient algorithm for clustering search engine results

AU - Zhang, Hui

AU - Pang, Bin

AU - Xie, Ke

AU - Wu, Hui

PY - 2007

Y1 - 2007

N2 - With the increasing number of Web documents in the Internet, the most popular keyword-matching-based 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.

AB - With the increasing number of Web documents in the Internet, the most popular keyword-matching-based 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.

UR - https://www.scopus.com/pages/publications/38349045521

U2 - 10.1007/978-3-540-74377-4_69

DO - 10.1007/978-3-540-74377-4_69

M3 - 会议稿件

AN - SCOPUS:38349045521

SN - 9783540743767

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 661

EP - 671

BT - Computational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers

PB - Springer Verlag

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

Y2 - 3 November 2006 through 6 November 2006

ER -

Zhang H, Pang B, Xie K, Wu H. An efficient algorithm for clustering search engine results. 在 Computational Intelligence and Security - International Conference, CIS 2006, Revised Selected Papers. Springer Verlag. 2007. 页码 661-671. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-74377-4_69

An efficient algorithm for clustering search engine results

摘要

出版系列

会议

访问文件

其它文件与链接

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引用此