Machine Learning
Vision in natural and virtual environments
ETRA '02 Proceedings of the 2002 symposium on Eye tracking research & applications
Machine Learning
The determinants of web page viewing behavior: an eye-tracking study
Proceedings of the 2004 symposium on Eye tracking research & applications
Eye-tracking analysis of user behavior in WWW search
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
The influence of task and gender on search and evaluation behavior using Google
Information Processing and Management: an International Journal
A quantitative analysis of lexical differences between genders in telephone conversations
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
What are you looking for?: an eye-tracking study of information usage in web search
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Feature forest models for probabilistic hpsg parsing
Computational Linguistics
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
Modeling latent biographic attributes in conversational genres
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Natural Language Processing with Python
Natural Language Processing with Python
Eye tracking as an MT evaluation technique
Machine Translation
A cognitive cost model of annotations based on eye-tracking data
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Improving gender classification of blog authors
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
A multi-pass sieve for coreference resolution
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Classifying latent user attributes in twitter
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
A comparison of features for automatic readability assessment
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Eye-tracking reveals the personal styles for search result evaluation
INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
Image registration for text-gaze alignment
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
Towards robust gaze-based objective quality measures for text
Proceedings of the Symposium on Eye Tracking Research and Applications
A real-time, multimodal, and dimensional affect recognition system
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Predicting academic emotions based on brainwaves, mouse behaviour and personality profile
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
Towards inferring language expertise using eye tracking
CHI '13 Extended Abstracts on Human Factors in Computing Systems
| Hi-index | 0.00 |
The reading act is an intimate and elusive process that is important to understand. Psycholinguists have long studied the effects of task, personal or document characteristics on reading behavior. An essential factor in the success of those studies lies in the capability of analyzing eye-movements. These studies aim to recognize causal effects on patterns of eye-movements, by contriving variations in task, personal or document characteristics. In this work, we follow the opposite direction. We present a formal framework to recognize reader's level of understanding and language skill given measurements of reading behavior via eye-gaze data. We show significant error reductions to recognize these attributes and provide a detailed study of the most discriminative features.