Inferring Document Readability by Integrating Eye Movement Features

Chen, Yongqiang; Zhang, Wenya; Song, Dawei; Zhang, Peng; Hou, Yuexian and Ren, Qingtao (2015). Inferring Document Readability by Integrating Eye Movement Features. In: SIGIR2015 Workshop on Neuro-Physiological Methods in IR Research, 13 Aug 2015, Santiago, Chile.

URL: https://docs.google.com/viewer?a=v&pid=sites&srcid...

Abstract

Capturing user’s emotional state is an emerging way for implicit relevance feedback in information retrieval (IR). Recently, EEG-based emotion recognition has drawn increasing attention. However, a key challenge is effective learning of useful features from EEG signals. In this paper, we present our on-going work on using Deep Belief Network (DBN) to automatically extract high-level features from raw EEG signals. Our preliminary experiment on the DEAP dataset shows that the learned features perform comparably to the use of manually generated features for emotion recognition.

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About

• Item ORO ID
• 44133
• Item Type
• Conference or Workshop Item
• Keywords
• information retrieval; readability prediction; eye movements
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 2015 The Authors
• Related URLs
• • https://sites.google.com/site/neuroir201...(Other)
  • http://sigir2015.org/(Other)
• Depositing User
• Dawei Song