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Query clustering using user logs
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DOI：10.1145/503104.503108.png)
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Abstract
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Query clustering is a process used to discover frequently asked questions or most popular topics on a search engine. This process is crucial for search engines based on question-answering. Because of the short lengths of queries, approaches based on keywords are not suitable for query clustering. This paper describes a new query clustering method that makes use of user logs which allow us to identify the documents the users have selected for a query. The similarity between two queries may be deduced from the common documents the users selected for them. Our experiments show that a combination of both keywords and user logs is better than using either method alone.
Keywords:
algorithms
experimentation
performance
query clustering
web data mining
user log
search engine
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