Hierarchical Clustering Based on Co-word for Web Information Retrieval

This paper proposes a novel method to generate labels for grouping and organizing the search results returned by auxiliary search engines. It has applied statistical techniques to measure the quantities of co-occurrence keywords for forming the label matrix of them, and then agglomerated them into higher-level clusters by clustering algorithm in order to classify the results which return from the source search engine. Compared with Lingo, the experimental results show that the labels generated by our algorithm are of more readability and generality. What's more, F-measure index also shows that our algorithm has improved the quality of text clustering to some extent.