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| An Improved Sequential IB Algorithm for Document Clustering |
| YE Yang-Dong, ZHANG Jie, LIU Dong |
| School of Information Engineering, Zhengzhou University, Zhengzhou 450052 |
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Abstract To solve the problems of local optima and low efficiency in sequential information bottleneck (sIB) algorithm for document clustering, an improved sIB algorithm is proposed, namely SA-isIB. By a reasonable annealing sequence, a certain proportional of documents are selected randomly from the initial clustering solution of basic sIB algorithm. Then the clustering labels of selected documents are revised and the solution is optimized iteratively. After the process of simulated annealing, higher accuracy document clustering solutions are obtained. Experimental results on document datasets show that by using SA-isIB algorithm the accuracy of sIB algorithm for document clustering is improved efficiently.
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Received: 06 March 2007
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2008, Vol. 21 
