The relationship between recall and precision
Journal of the American Society for Information Science
Automatically organizing bookmarks per contents
Proceedings of the fifth international World Wide Web conference on Computer networks and ISDN systems
User interface directions for the Web
Communications of the ACM
Internet browsing and searching: user evaluations of category map and concept space techniques
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
Real life, real users, and real needs: a study and analysis of user queries on the web
Information Processing and Management: an International Journal
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science
Using clustering techniques to detect usage patterns in a Web-based information system
Journal of the American Society for Information Science and Technology
Data Mining Techniques: For Marketing, Sales, and Customer Support
Data Mining Techniques: For Marketing, Sales, and Customer Support
On Clustering Validation Techniques
Journal of Intelligent Information Systems
The Inmates Are Running the Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity (2nd Edition)
Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
Dynamic web log session identification with statistical language models
Journal of the American Society for Information Science and Technology - Special issue: Webometrics
A new approach to intranet search based on information extraction
Proceedings of the 14th ACM international conference on Information and knowledge management
Web Search: Public Searching of the Web (Information Science and Knowledge Management)
Web Search: Public Searching of the Web (Information Science and Knowledge Management)
The search experience variable in information behavior research
Journal of the American Society for Information Science and Technology
End-point detection of the aerobic phase in a biological reactor using SOM and clustering algorithms
Engineering Applications of Artificial Intelligence
Self-Organizing map clustering analysis for molecular data
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Clustering of the self-organizing map
IEEE Transactions on Neural Networks
Survey of clustering algorithms
IEEE Transactions on Neural Networks
AIRS '09 Proceedings of the 5th Asia Information Retrieval Symposium on Information Retrieval Technology
Simulating simple and fallible relevance feedback
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Proceedings of the 39th annual ACM SIGUCCS conference on User services
Time drives interaction: simulating sessions in diverse searching environments
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
How doctors search: A study of query behaviour and the impact on search results
Information Processing and Management: an International Journal
Mixing and matching usage data: techniques for mining varied activity data sources
Proceedings of the 41st annual ACM SIGUCCS conference on User services
Modelling user behaviour and experience: the R2D2 networks approach
DUXU'13 Proceedings of the Second international conference on Design, User Experience, and Usability: design philosophy, methods, and tools - Volume Part I
Effectiveness of search result classification based on relevance feedback
Journal of Information Science
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When studying how ordinary Web users interact with Web search engines, researchers tend to either treat the users as a homogeneous group or group them according to search experience. Neither approach is sufficient, we argue, to capture the variety in behavior that is known to exist among searchers. By applying automatic clustering technique based on self-organizing maps to search engine log files from a corporate intranet, we show that users can be usefully separated into distinguishable segments based on their actual search behavior. Based on these segments, future tools for information seeking and retrieval can be targeted to specific segments rather than just made to fit the “the average user.” The exact number of clusters, and to some extent their characteristics, can be expected to vary between intranets, but our results indicate that some more generic groups may exist. In our study, a large group of users appeared to be “fact seekers” who would benefit from higher precision, a smaller group of users were more holistically oriented and would likely benefit from higher recall, and a third category of users seemed to constitute the knowledgeable users. These three groups may raise different design implications for search-tool developers. © 2008 Wiley Periodicals, Inc.