Building Domain-Specific Search Engines with Machine Learning Techniques

Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore

Domain-specific search engines are growing in popularity because they offer increased accuracy and extra functionality not possible with the general, Web-wide search engines. For example, allows complex queries by age-group, size, location and cost over summer camps. Unfortunately these domain-specific search engines are difficult and timeconsuming to maintain. This paper proposes the use of machine learning techniques to greatly automate the creation and maintenance of domain-specific search engines.

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