Paper Info
Title
Quantitative analysis and inference on gaze data using natural language processing techniques
Abstract
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.
Year
DOI
Venue
2012
10.1145/2166966.2167055
IUI
Keywords
Field
DocType
natural language processing technique,human-machine interaction,human behavior,on-line adaptation capability,quantitative analysis,hypothesis testing,information need,robust framework,user model,eye-tracking device,user-centered information system,information system,hypothesis test,feature extraction,data collection,natural language processing,eye tracking
Information system,Information needs,Inference,Computer science,Usability,Feature extraction,Human–computer interaction,Natural language processing,Artificial intelligence,User modeling,Statistical hypothesis testing,Knowledge acquisition
Conference
Citations 
PageRank 
References 
2
0.39
4
Authors
1
Name
Order
Citations
PageRank
Pascual Martinez-Gomez181.60