Clustering method based on concept and semantic similarity
Jiao Fenfen · Computer Engineering and Applications Journal · 2012
This paper introduces a new document clustering method using concept and semantic similarity—Text Clustering Based on Concept and Semantic Similarity(TCBCSS).Key concept is extracted,instead of the keyword,to form semantic network.The semantic network is analyzed using Six Degrees of Separation and geometric characteristics,to build concept lists,which represent the document.This not only resolves the problem of differentially expressed,but also is more convenient for similarity computation.TCBCSS algorithm uses semantic similarity of concept lists as a measure of similarity between the two documents,and clusters the document based on graph,to avoid some limitations of the clustering algorithm on the clustered shape.Experimental results prove that TCBCSS algorithm improves the quality of the clustering.