Concept Association Mining Based on Clustering and Association Rules
In order to solve the difficult concept association mining of query keywords in the semantic search, it raises a method of extracting concept association based on hierarchical clustering and association rules. Firstly, quick updating algorithm of association rules is adopted to extract non-categorization relationships of key words in the paper. Meanwhile, improved method of hierarchical clustering is used for the extraction of categorization relation while how to find father node for leaf nodes of the hierarchical clustering tree is provided as well. The experiment shows that, with such method, it can not only improve the accuracy rate of extraction of key word concept association but also has an important significance to the enhancement of precision as well as range of semantic search.
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