Term Ranking for Clustering Web Search Results

  title={Term Ranking for Clustering Web Search Results},
  author={Fatih Gelgi and Hasan Davulcu and Srinivas Vadrevu},
Clustering web search engine results for ambiguous keyword searches poses unique challenges. First, we show that one cannot readily import the frequency based feature ranking to cluster the web search results as in the text document clustering. Next, we present TermRank, a variation of the PageRank algorithm based on a relational graph representation of the content of web document collections. TermRank achieves desirable ranking of discriminative terms higher than the ambiguous terms, and… CONTINUE READING
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