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Classifying the user intent of web queries using k-means clustering

11 years 3 days ago
Classifying the user intent of web queries using k-means clustering
Purpose – Web search engines are frequently used by people to locate information on the Internet. However, not all queries have an informational goal. Instead of information, some people may be looking for specific web sites or may wish to conduct transactions with web services. This paper aims to focus on automatically classifying the different user intents behind web queries. Design/methodology/approach – For the research reported in this paper, 130,000 web search engine queries are categorized as informational, navigational, or transactional using a k-means clustering approach based on a variety of query traits. Findings – The research findings show that more than 75 percent of web queries (clustered into eight classifications) are informational in nature, with about 12 percent each for navigational and transactional. Results also show that web queries fall into eight clusters, six primarily informational, and one each of primarily transactional and navigational. Research ...
Ashish Kathuria, Bernard J. Jansen, Carolyn Hafern
Added 28 Jan 2011
Updated 28 Jan 2011
Type Journal
Year 2010
Where INTR
Authors Ashish Kathuria, Bernard J. Jansen, Carolyn Hafernik, Amanda Spink
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