Predicting Source Gaze Fixation duration

OPEN ARCHIVE

Union Jack
Dannebrog

Predicting Source Gaze Fixation duration

Vis flere oplysninger

Titel: Predicting Source Gaze Fixation duration
A Machine Learning Approach
Forfatter: Saikh, Tanik; Bangalore, Srinivas; Carl, Michael; Bandyopadhyay, Sivaji
Resume: In this paper an attempt has been made to predict the gaze fixation duration at source text using supervised learning techniques. 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.
URI: http://hdl.handle.net/10398/9121
Dato: 2015-04-23
Note: Paper presented at the 2015 International Conference on Cognitive Computing and Information Processing. 3-4 March 2015. Noida, Indien

Creative Commons License This work is licensed under a Creative Commons License.

Filer Størrelse Format Vis
Carl.pdf 267.2Kb PDF Vis/Åbn Conference paper

Dette dokument findes i følgende samling(er)

Vis flere oplysninger