ISTC: A New Method for Clustering Search Results

【摘要】 A new common phrase scoring method is proposed according to term frequency-inverse document frequency (TFIDF) and independence of the phrase. Combining the two properties can help identify more reasonable common phrases, which improve the accuracy of clustering. Also, the equation to measure the in-dependence of a phrase is proposed in this paper. The new algo-rithm which improves suffix tree clustering algorithm (STC) is named as improved suffix tree clustering (ISTC). To validate the proposed algorithm, a prototype system is implemented and used to cluster several groups of web search results obtained from Google search engine. Experimental results show that the im-proved algorithm offers higher accuracy than traditional suffix tree clustering.更多还原

【Abstract】 A new common phrase scoring method is proposed according to term frequency-inverse document frequency (TFIDF) and independence of the phrase. Combining the two properties can help identify more reasonable common phrases, which improve the accuracy of clustering. Also, the equation to measure the in-dependence of a phrase is proposed in this paper. The new algo-rithm which improves suffix tree clustering algorithm (STC) is named as improved suffix tree clustering (ISTC). To validate the proposed algorithm, a prototype system is implemented and used to cluster several groups of web search results obtained from Google search engine. Experimental results show that the im-proved algorithm offers higher accuracy than traditional suffix tree clustering.更多还原