The World-Wide Web: quagmire or gold mine?
Communications of the ACM
ACM SIGKDD Explorations Newsletter
Eye Tracking Methodology: Theory and Practice
Eye Tracking Methodology: Theory and Practice
A new "wireless" search-coil system
Proceedings of the 2008 symposium on Eye tracking research & applications
Best practices for eye tracking of television and video user experiences
Proceedings of the 1st international conference on Designing interactive user experiences for TV and video
Visual complexity and aesthetic perception of web pages
Proceedings of the 26th annual ACM international conference on Design of communication
What do you see when you're surfing?: using eye tracking to predict salient regions of web pages
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Computational visual attention systems and their cognitive foundations: A survey
ACM Transactions on Applied Perception (TAP)
Design and Implementation of a Methodology for Identifying Website Keyobjects
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Eyetracking Web Usability
The good, the bad, and the random: an eye-tracking study of ad quality in web search
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Eye Movement Analysis for Activity Recognition Using Electrooculography
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extracting significant Website Key Objects: A Semantic Web mining approach
Engineering Applications of Artificial Intelligence
Web mining in soft computing framework: relevance, state of the art and future directions
IEEE Transactions on Neural Networks
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
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This paper introduces a novel approach for collecting and processing data originated by web user ocular movements on a web page, which are captured by using an eye-tracking tool. These data allow knowing the exact web user's eye position on a computer screen, and by combining them with the sequence of web page visits registered in the web log, significant insights about his/her behavior within a website can be extracted. With this approach, we can improve the effectiveness of the current methodology for identifying the most important web objects from the web user's point of view, also called Website Keyobjects. It takes as input the website's logs, the pages that compose it and the interest of users in the web objects of each page, which is quantified by means of a survey. Subsequently, the data are transformed and preprocessed before finally applying web mining algorithms that allow the extraction of the Website Keyobjects. With the utilization of the eye-tracking technology, we can eliminate the survey by using a more precise and objective tool to achieve an improvement in the classification of the Website Keyobjects. It was concluded that eye-tracking technology is useful and accurate when it comes to knowing what a user looks at and therefore, what attracts their attention the most. Finally, it was established that there is an improvement between 15% and 20% when using the information generated by the eye tracker.