USING CLUSTERING TECHNOLOGY TO IMPROVE XML SEMANTIC SEARCH

摘要：

To get semantic related searching results based on simple keywords, XML search engine not only need to search the matched nodes but also need to check whether those matched nodes are semantic related nodes in XML tree. Since the judgment on the semantic related nodes might cost much time, we first use mining technology to cluster XML documents and compute the similarity between query and XML clusters so as to filter the unrelated clusters with the query. To get exact clusters, we use all paths less than or equal to length L as feature vectors for XML document. We also use bipartite graph to express feature vector matrix and use adjacency list to store the bipartite graph. Based on this idea, we improved the path-based XML clustering algorithm. We use common paths as the feature of cluster and give the similarity measure between query and clusters.

关键词： XML Clustering Path Feature Semantic Search Adjacency List

作者: XIN-YE LI

作者单位: Department of Electronic and Communication Engineering, North China Electric Power University, Baoding, Hebei ,071003,P.R.China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2635-2639

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）