A fast and effective method for clustering large-scale Chinese question dataset

CORC > 北京大学 > 信息科学技术学院

	A fast and effective method for clustering large-scale Chinese question dataset
	Zhang, Xiaodong ; Wang, Houfeng
刊名	communications in computer and information science
	2014
英文摘要	Question clustering plays an important role in QA systems. Due to data sparseness and lexical gap in questions, there is no sufficient information to guarantee good clustering results. Besides, previous works pay little attention to the complexity of algorithms, resulting in infeasibility on large-scale datasets. In this paper, we propose a novel similarity measure, which employs word relatedness as additional information to help calculating similarity between questions. Based on the similarity measure and k-means algorithm, semantic k-means algorithm and its extended version are proposed. Experimental results show that the proposed methods have comparable performance with state-of-the-art methods and cost less time. ? Springer-Verlag Berlin Heidelberg 2014.; EI; 0; 345-356; 496
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/327890]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Xiaodong,Wang, Houfeng. A fast and effective method for clustering large-scale Chinese question dataset[J]. communications in computer and information science,2014.
APA	Zhang, Xiaodong,&Wang, Houfeng.(2014).A fast and effective method for clustering large-scale Chinese question dataset.communications in computer and information science.
MLA	Zhang, Xiaodong,et al."A fast and effective method for clustering large-scale Chinese question dataset".communications in computer and information science (2014).