Work place: Institute of Science & Technology Information of China, Beijing, China
E-mail: fxsteve@163.com
Website:
Research Interests: Applied computer science, Computational Science and Engineering, Computer systems and computational processes, Theoretical Computer Science
Biography
Qingwei Shi was born in fuxin,China in 1973, earned B.S. degree in the field of management from Dalian Maritime University in 1995 and M.S. degree in the field of computer science & technology from Shenyang University of Technology in 2001, earned Ph.D. degree in the field of computer science & technology from Tianjin University in 2008.
He is now a teacher at school of software in Liaoning Technical University(LNTU). Before joining the LNTU, he was a software engineer in GKT corporation for about 3 years. Recently he has published 10 researh papers in the area of text mining.
By Qingwei Shi Xiaodong Qiao Xu Guangquan
DOI: https://doi.org/10.5815/ijitcs.2010.02.06, Pub. Date: 8 Dec. 2010
In this paper, we present a string kernel based method for documents clustering. Documents are viewed as sequences of strings, and documents similarity is calculated by the kernel function. According to the documents similarity, spectral clustering algorithm is used to group documents. Experimental results shows that string kernel method outperform the standard k-means algorithm on the Reuters-21578 dataset.
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