Visualizing implicit queries for information management and retrieval
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
User interactions with everyday applications as context for just-in-time information access
Proceedings of the 5th international conference on Intelligent user interfaces
SUITOR: an attentive information system
Proceedings of the 5th international conference on Intelligent user interfaces
Proceedings of the 6th international conference on Intelligent user interfaces
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Communications of the ACM
The Relationship between Scene and Eye Movements
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume 5 - Volume 5
Kernel partial least squares regression in reproducing kernel hilbert space
The Journal of Machine Learning Research
Implicit feedback for inferring user preference: a bibliography
ACM SIGIR Forum
Implicit queries (IQ) for contextualized search
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
EyeWindows: evaluation of eye-controlled zooming windows for focus selection
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluating implicit measures to improve web search
ACM Transactions on Information Systems (TOIS)
Combining eye movements and collaborative filtering for proactive information retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Accurately interpreting clickthrough data as implicit feedback
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
User performance versus precision measures for simple search tasks
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Eye-tracking for user modeling in exploratory learning environments: An empirical evaluation
Knowledge-Based Systems
Implicit relevance feedback from eye movements
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Image ranking with implicit feedback from eye movements
Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications
Inferring word relevance from eye-movements of readers
Proceedings of the 16th international conference on Intelligent user interfaces
Attentive documents: Eye tracking as implicit feedback for information retrieval and beyond
ACM Transactions on Interactive Intelligent Systems (TiiS)
What do you want to do next: a novel approach for intent prediction in gaze-based interaction
Proceedings of the Symposium on Eye Tracking Research and Applications
Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design
Adaptive visualization for exploratory information retrieval
Information Processing and Management: an International Journal
Feature selection for gaze, pupillary, and EEG signals evoked in a 3D environment
Proceedings of the 6th workshop on Eye gaze in intelligent human machine interaction: gaze in multimodal interaction
| Hi-index | 0.00 |
We study a new research problem, where an implicit information retrieval query is inferred from eye movements measured when the user is reading, and used to retrieve new documents. In the training phase, the user's interest is known, and we learn a mapping from how the user looks at a term to the role of the term in the implicit query. Assuming the mapping is universal, that is, the same for all queries in a given domain, we can use it to construct queries even for new topics for which no learning data is available. We constructed a controlled experimental setting to show that when the system has no prior information as to what the user is searching, the eye movements help significantly in the search. This is the case in a proactive search, for instance, where the system monitors the reading behaviour of the user in a new topic. In contrast, during a search or reading session where the set of inspected documents is biased towards being relevant, a stronger strategy is to search for content-wise similar documents than to use the eye movements.