Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization

Shi Cheng; Yuhui Shi; Quande Qin; T. O. Ting

doi:10.1109/SIS.2013.6615174

Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization

Shi Cheng, Yuhui Shi, Quande Qin, T. O. Ting

Department of Electrical and Electronic Engineering

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

3 Citations (Scopus)

Abstract

In this paper, the nearest neighbor method on Chinese text categorization is formulated as an optimization problem. The particle swarm optimization is utilized to optimize a nearest neighbor classifier to solve the Chinese text categorization problem. The parameter k was first optimized to obtain the minimum error, then the categorization problem is formulated as a discrete, constrained, and single objective optimization problem. Each dimension of solution vector is dependent on each other in the solution space. The parameter k and the number of labeled examples for each class are optimized together to reach the minimum categorization error. In the experiment, with the utilization of particle swarm optimization, the performance of a nearest neighbor algorithm can be improved, and the algorithm can obtain the minimum categorization error rate.

Original language	English
Title of host publication	Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Pages	164-171
Number of pages	8
DOIs	https://doi.org/10.1109/SIS.2013.6615174
Publication status	Published - 2013
Event	2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 - Singapore, Singapore Duration: 16 Apr 2013 → 19 Apr 2013

Publication series

Name	Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

Conference

Conference	2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013
Country/Territory	Singapore
City	Singapore
Period	16/04/13 → 19/04/13

Keywords

Particle swarm optimization
k-weighted nearest neighbor
nearest neighbor
parameter optimization
text categorization

Access to Document

10.1109/SIS.2013.6615174

Cite this

Cheng, S., Shi, Y., Qin, Q., & Ting, T. O. (2013). Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization. In Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 (pp. 164-171). Article 6615174 (Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013). https://doi.org/10.1109/SIS.2013.6615174

Cheng, Shi ; Shi, Yuhui ; Qin, Quande et al. / Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization. Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. 2013. pp. 164-171 (Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013).

@inproceedings{f06cf82f82204972bcddc91c8f007e3a,

title = "Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization",

abstract = "In this paper, the nearest neighbor method on Chinese text categorization is formulated as an optimization problem. The particle swarm optimization is utilized to optimize a nearest neighbor classifier to solve the Chinese text categorization problem. The parameter k was first optimized to obtain the minimum error, then the categorization problem is formulated as a discrete, constrained, and single objective optimization problem. Each dimension of solution vector is dependent on each other in the solution space. The parameter k and the number of labeled examples for each class are optimized together to reach the minimum categorization error. In the experiment, with the utilization of particle swarm optimization, the performance of a nearest neighbor algorithm can be improved, and the algorithm can obtain the minimum categorization error rate.",

keywords = "Particle swarm optimization, k-weighted nearest neighbor, nearest neighbor, parameter optimization, text categorization",

author = "Shi Cheng and Yuhui Shi and Quande Qin and Ting, {T. O.}",

year = "2013",

doi = "10.1109/SIS.2013.6615174",

language = "English",

isbn = "9781467360043",

series = "Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013",

pages = "164--171",

booktitle = "Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013",

note = "2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013 ; Conference date: 16-04-2013 Through 19-04-2013",

}

Cheng, S, Shi, Y, Qin, Q & Ting, TO 2013, Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization. in Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013., 6615174, Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, pp. 164-171, 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013, Singapore, Singapore, 16/04/13. https://doi.org/10.1109/SIS.2013.6615174

Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization. / Cheng, Shi; Shi, Yuhui; Qin, Quande et al.
Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. 2013. p. 164-171 6615174 (Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013).

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

TY - GEN

T1 - Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization

AU - Cheng, Shi

AU - Shi, Yuhui

AU - Qin, Quande

AU - Ting, T. O.

PY - 2013

Y1 - 2013

N2 - In this paper, the nearest neighbor method on Chinese text categorization is formulated as an optimization problem. The particle swarm optimization is utilized to optimize a nearest neighbor classifier to solve the Chinese text categorization problem. The parameter k was first optimized to obtain the minimum error, then the categorization problem is formulated as a discrete, constrained, and single objective optimization problem. Each dimension of solution vector is dependent on each other in the solution space. The parameter k and the number of labeled examples for each class are optimized together to reach the minimum categorization error. In the experiment, with the utilization of particle swarm optimization, the performance of a nearest neighbor algorithm can be improved, and the algorithm can obtain the minimum categorization error rate.

AB - In this paper, the nearest neighbor method on Chinese text categorization is formulated as an optimization problem. The particle swarm optimization is utilized to optimize a nearest neighbor classifier to solve the Chinese text categorization problem. The parameter k was first optimized to obtain the minimum error, then the categorization problem is formulated as a discrete, constrained, and single objective optimization problem. Each dimension of solution vector is dependent on each other in the solution space. The parameter k and the number of labeled examples for each class are optimized together to reach the minimum categorization error. In the experiment, with the utilization of particle swarm optimization, the performance of a nearest neighbor algorithm can be improved, and the algorithm can obtain the minimum categorization error rate.

KW - Particle swarm optimization

KW - k-weighted nearest neighbor

KW - nearest neighbor

KW - parameter optimization

KW - text categorization

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DO - 10.1109/SIS.2013.6615174

M3 - Conference Proceeding

AN - SCOPUS:84886801753

SN - 9781467360043

T3 - Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

SP - 164

EP - 171

BT - Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

T2 - 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013

Y2 - 16 April 2013 through 19 April 2013

ER -

Cheng S, Shi Y, Qin Q, Ting TO. Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization. In Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013. 2013. p. 164-171. 6615174. (Proceedings of the 2013 IEEE Symposium on Swarm Intelligence, SIS 2013 - 2013 IEEE Symposium Series on Computational Intelligence, SSCI 2013). doi: 10.1109/SIS.2013.6615174

Particle swarm optimization based nearest neighbor algorithm on Chinese text categorization

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