A test of task-technology fit theory for group support systems
ACM SIGMIS Database
Implicit user modeling for personalized search
Proceedings of the 14th ACM international conference on Information and knowledge management
TREC: Experiment and Evaluation in Information Retrieval (Digital Libraries and Electronic Publishing)
Mining long-term search history to improve search accuracy
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
IIiX Proceedings of the 1st international conference on Information interaction in context
SearchBar: a search-centric web history for task resumption and information re-finding
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A system for adaptive information retrieval
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
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We present a personalised retrieval system that captures explicit relevance feedback to build an evolving user profile with multiple aspects. The user profile is used to proactively retrieve results between search sessions to support multi-session search tasks. This approach to supporting users with their multi-session search tasks is evaluated in a between-subjects multiple time-series study with ten subjects performing two simulated work situation tasks over five sessions. System interaction data shows that subjects using the personalised retrieval system issue fewer queries and interact with fewer results than subjects using a baseline system. The interaction data also shows a trend of subjects interacting with the proactively retrieved results in the personalised retrieval system.