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
UR - https://www.scopus.com/pages/publications/84886801753
U2 - 10.1109/SIS.2013.6615174
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 -