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In this paper, we report ongoing efforts in a large scale research project to develop methods for profiling individual Web search engine users by leveraging data recorded in the transaction logs of search engines. Our research aim is to investigate how completely one can profile a Web searcher using log data. Taking a broad brush approach, we present an array of profiling attributes to illustrate the spectrum of user characteristics possible from log data. Specifically, we present ongoing...
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This report summarises a workshop organised as a part of the EU-funded TrebleCLEF project entitled "Query Log Analysis: From Research to Best Practice" held on 27-28th May 2009 at the British Computer Science Offices in London, UK. The event involved 12 invited speakers from various academic and commercial institutions from around the world who are all involved, in some way, with query log analysis. A number of other people attended the event including local businesses and academic...
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Query reformulation is a key user behavior during Web search. Our research goal is to develop predictive models of query reformulation during Web searching. This article reports results from a study in which we automatically classified the query-reformulation patterns for 964,780 Web searching sessions, composed of 1,523,072 queries, to predict the next query reformulation. We employed an n-gram modeling approach to describe the probability of users transitioning from one query-reformulation...
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