A genetic K-means approaches for automated Web page classification

Dehu Qi; Bo Sun

A genetic K-means approaches for automated Web page classification

Dehu Qi, Bo Sun

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

Abstract

This paper presents a new genetic K-means approach. Instead of evolving the centroid population, this new approach evolves the weights associated with the keywords, which character each class. The approach is implemented as a hierarchical automated web page classifier for automated web page classification. Initial experimental results are very promising and easy to expand to further classification.

Original language	English (US)
Title of host publication	Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004
Editors	A.M. Memon, N. Zhao
Pages	241-246
Number of pages	6
State	Published - 2004
Externally published	Yes
Event	Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004 - Las Vegas, NV, United States Duration: Nov 8 2004 → Nov 10 2004

Publication series

Name	Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004

Other

Other	Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004
Country/Territory	United States
City	Las Vegas, NV
Period	11/8/04 → 11/10/04

All Science Journal Classification (ASJC) codes

General Engineering

Cite this

@inproceedings{9f2d23a71e194e83ae121500dd94d21a,

title = "A genetic K-means approaches for automated Web page classification",

abstract = "This paper presents a new genetic K-means approach. Instead of evolving the centroid population, this new approach evolves the weights associated with the keywords, which character each class. The approach is implemented as a hierarchical automated web page classifier for automated web page classification. Initial experimental results are very promising and easy to expand to further classification.",

author = "Dehu Qi and Bo Sun",

year = "2004",

language = "English (US)",

isbn = "0780388194",

series = "Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004",

pages = "241--246",

editor = "A.M. Memon and N. Zhao",

booktitle = "Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004",

note = "Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004 ; Conference date: 08-11-2004 Through 10-11-2004",

}

Qi, D & Sun, B 2004, A genetic K-means approaches for automated Web page classification. in AM Memon & N Zhao (eds), Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004. Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004, pp. 241-246, Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004, Las Vegas, NV, United States, 11/8/04.

A genetic K-means approaches for automated Web page classification. / Qi, Dehu; Sun, Bo.
Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004. ed. / A.M. Memon; N. Zhao. 2004. p. 241-246 (Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004).

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

TY - GEN

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AU - Qi, Dehu

AU - Sun, Bo

PY - 2004

Y1 - 2004

N2 - This paper presents a new genetic K-means approach. Instead of evolving the centroid population, this new approach evolves the weights associated with the keywords, which character each class. The approach is implemented as a hierarchical automated web page classifier for automated web page classification. Initial experimental results are very promising and easy to expand to further classification.

AB - This paper presents a new genetic K-means approach. Instead of evolving the centroid population, this new approach evolves the weights associated with the keywords, which character each class. The approach is implemented as a hierarchical automated web page classifier for automated web page classification. Initial experimental results are very promising and easy to expand to further classification.

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M3 - Conference contribution

AN - SCOPUS:16244415582

SN - 0780388194

T3 - Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004

SP - 241

EP - 246

BT - Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004

A2 - Memon, A.M.

A2 - Zhao, N.

T2 - Proceedings of the 2004 IEEE International Conference on Information Reuse and Integration, IRI-2004

Y2 - 8 November 2004 through 10 November 2004

ER -

A genetic K-means approaches for automated Web page classification

Abstract

Publication series

Other

All Science Journal Classification (ASJC) codes

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Cite this