Title :
An Effective Search Results Semantic Optimization Clustering Method for XML Fragments
Author_Institution :
Sch. of Inf. Technol., Jiangxi Univ. of Finance & Econ., Nanchang, China
Abstract :
With the emergence of more and more XML documents, the clustering of XML documents has become an active research area. However, it is more significance of XML element clustering than whole document due to the more focused and specific amount of information, especially to some application domain. Therefore, in this paper, we study the xml element clustering, in which the latent semantic indexing model is used to obtain the semantic relationship between terms firstly, and then a evaluation function for k-mediod is presented to automatic generate the optimal cluster number. In addition, information gain, for evaluating clustering quality is introduced. Experiment results show that the proposed semantic clustering optimization method outperforms the traditional method (No_optimization) in information gain and produces better clustering quality.
Keywords :
XML; document handling; indexing; information retrieval; pattern clustering; XML documents; XML fragments; clustering quality; document clustering; evaluation function; k-mediod; latent semantic indexing model; search results; semantic optimization clustering method; Clustering algorithms; Indexing; Mathematical model; Optimization methods; Semantics; XML; Evaluation Function; Optimal Cluster Number; Search Results Clustering; XML Fragments;
Conference_Titel :
Computer Sciences and Applications (CSA), 2013 International Conference on
Conference_Location :
Wuhan
DOI :
10.1109/CSA.2013.117