Identification of factors predicting clickthrough in Web searching using neural network analysis
Journal of the American Society for Information Science and Technology
Analyzing and evaluating query reformulation strategies in web search logs
Proceedings of the 18th ACM conference on Information and knowledge management
The semantics of query modification
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
Explaining query modifications: an alternative interpretation of term addition and removal
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
Analyzing and mining a code search engine usage log
Empirical Software Engineering
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This article reports on the development of a novel method for the analysis of Web logs. The method uses techniques that look for similarities between queries and identify sequences of “query transformation”. It allows sequences of query transformations to be represented as graphical networks, thereby giving a richer view of search behavior than is possible with the usual sequential descriptions. We also perform a basic analysis to study the correlations between observed transformation codes, with results that appear to show evidence of behavior habits. The method was developed using transaction logs from the Excite search engine to provide a tool for an ongoing research project that is endeavoring to develop a greater understanding of Web-based searching by the general public. © 2007 Wiley Periodicals, Inc.