Patterns of search: analyzing and modeling Web query refinement
UM '99 Proceedings of the seventh international conference on User modeling
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We present a knowledge discovery tool Search Excavator (SE) developed for detecting similar words in web documents ranked by overall usage frequency in American English. The SE prototype application is a web browser add-on developed to assist users in acquiring new knowledge in unknown domains and to help in posing more specific search queries. The SE is designed to discover similar but generally infrequent words with surrounding texts in browser web documents and then suggest found words as possible query keywords. This technique allows users to discover unknown data intersections and use less ambiguous queries to target the required documents. The SE concept is motivated by a number of ideas. The similar infrequent words in the texts of the relevant documents can include field specific terms and facts that can be unknown to the user. Suggesting such keywords can decrease the overall search time encouraging early learning by directing users to the new unknown relevant terms and facts in a search session with an ambiguous query. Finally, we present four demonstration scenarios from our small-scale qualitative user study of the SE tool.