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Inducing Word Senses to Improve Web Search Result Clustering by Roberto Navigli ; Giuseppe Crisafulli is a scholarly article available to read on EtoBox.
What is Inducing Word Senses to Improve Web Search Result Clustering about?
In this paper, we present a novel approach to Web search result clustering based on the automatic discovery of word senses from raw text, a task referred to as Word Sense Induction (WSI). We first acquire the senses (i.e., meanings) of a query by means of a graphbased clustering algorithm that exploits cycles (triangles and squares) in the co-occurrence graph of the query. Then we cluster the search results based on their semantic similarity to the induced word senses. Our experiments, conducted on datasets of ambiguous queries, show that our approach improves search result clustering in terms of both clustering quality and degree of diversification.
- Author
- Roberto Navigli ; Giuseppe Crisafulli
- Published
- 1970
- Language
- EN