TY - GEN
T1 - Novel hybrid document clustering algorithm based on Ant Colony and Agglomerate
AU - Wang, Xiaohua
AU - Shen, Jie
AU - Tang, Hongjun
PY - 2009
Y1 - 2009
N2 - In this paper, Ant Colony algorithm was improved from two aspects, then a novel Hybrid Ant Colony and Agglomerate document clustering algorithm, Hybrid- AC&A, has been proposed based on Ant Colony Model and agglomerate clustering algorithms. Firstly, Compact Algorithm was applied while ant dropping its load. Secondly, evaluate function based schedule algorithm was applied while ant obtains load. Finally, Agglomerate clustering algorithm was integrated into the iteration procedure of Ant Colony clustering algorithm. The performance of Hybrid- AC&A is compared with other clustering methods, the experimental results denote that the proposed algorithm not only inherits the intrinsic advantages of ant colony model clustering algorithm, but also improves the aspect of time efficiency. Computational result on real documents collection shows it is much more efficient than other mentioned algorithms.
AB - In this paper, Ant Colony algorithm was improved from two aspects, then a novel Hybrid Ant Colony and Agglomerate document clustering algorithm, Hybrid- AC&A, has been proposed based on Ant Colony Model and agglomerate clustering algorithms. Firstly, Compact Algorithm was applied while ant dropping its load. Secondly, evaluate function based schedule algorithm was applied while ant obtains load. Finally, Agglomerate clustering algorithm was integrated into the iteration procedure of Ant Colony clustering algorithm. The performance of Hybrid- AC&A is compared with other clustering methods, the experimental results denote that the proposed algorithm not only inherits the intrinsic advantages of ant colony model clustering algorithm, but also improves the aspect of time efficiency. Computational result on real documents collection shows it is much more efficient than other mentioned algorithms.
KW - Agglomerate
KW - Ant colony
KW - Document clustering
UR - https://www.scopus.com/pages/publications/77951019865
U2 - 10.1109/KAM.2009.182
DO - 10.1109/KAM.2009.182
M3 - Conference contribution
AN - SCOPUS:77951019865
SN - 9780769538884
T3 - 2009 2nd International Symposium on Knowledge Acquisition and Modeling, KAM 2009
SP - 65
EP - 68
BT - 2009 2nd International Symposium on Knowledge Acquisition and Modeling, KAM 2009
T2 - 2009 2nd International Symposium on Knowledge Acquisition and Modeling, KAM 2009
Y2 - 30 November 2009 through 1 December 2009
ER -