Query expansion using gaze-based feedback on the subdocument level
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Personalized online document, image and video recommendation via commodity eye-tracking
Proceedings of the 2008 ACM conference on Recommender systems
User-oriented document summarization through vision-based eye-tracking
Proceedings of the 14th international conference on Intelligent user interfaces
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Hi-index | 0.00 |
Eye-tracking devices find applications in human-machine interaction, hypothesis testing in psycholinguistic and usability studies, relevant feature extraction when designing models related to human behavior and to build user-centered information systems. We aim at providing a general and robust framework to do quantitative analysis and inference using data collected by eye-trackers when users read text. To achieve this objective, first the accuracy of eye-trackers has to be increased beyond sensor capabilities by using information from the content or the structure of the text. Then, natural language processing techniques will be used to process text appearing on the screen and the recognized reading word sequence. Within this framework, it will be possible to better understand user's intentions, record knowledge acquisition and predict information needs. The intention is to build a user model and user model of the World from texts that users have read. This opens the door to more personalized systems with on-line adaptation capabilities.