Journal of the American Society for Information Science
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Journal of the American Society for Information Science and Technology
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Applying web usage mining for adaptive intranet navigation
IRFC'11 Proceedings of the Second international conference on Multidisciplinary information retrieval facility
Looking for genre: the use of structural features during search tasks with Wikipedia
Proceedings of the 4th Information Interaction in Context Symposium
You have e-mail, what happens next? Tracking the eyes for genre
Information Processing and Management: an International Journal
Hi-index | 0.00 |
The problems of comparing search support tool in interactive information retrieval (IIR) and of selecting the right one have always been difficult due to the inherent dependency to users. Using an adapted evaluation protocol, we study in this paper different suggestion approaches. The results show that the performance are changing for different users and also during the search sessions. As a consequence, they also show that the selection of a particular support tool has to use new grounding. In this way, we propose a system that allows to combine independent suggestion mechanisms based on an analysis of user behavior and considering the search session time as a key factor instead of using only static rules.