Abstract
In this paper an attempt has been made to predict the gaze fixation duration at source text words using supervised learning method, namely Support Vector Machine. The machine learning models used in the present work make use of lexical, syntactic and semantic information for predicting the gaze fixation duration. Different features are extracted from the data and models are built by combining the features. Our best set up achieves close to 50% classification accuracy.
| Original language | English |
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| Publication date | 3 Mar 2015 |
| Number of pages | 6 |
| Publication status | Published - 3 Mar 2015 |
| Event | 2015 International Conference on Cognitive Computing and Information Processing - JSS Academy of Technical Education, Noida, India Duration: 3 Mar 2015 → 3 Mar 2015 http://www.ccip.jssaten.ac.in/ |
Conference
| Conference | 2015 International Conference on Cognitive Computing and Information Processing |
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| Location | JSS Academy of Technical Education |
| Country/Territory | India |
| City | Noida |
| Period | 03/03/2015 → 03/03/2015 |
| Sponsor | JSS Academy of Technical Education, Noida |
| Internet address |
Keywords
- Support Vector Machine
- Eye Tracking
- Gaze Fixation Duration
- Machine Learning