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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.

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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.

Item Type: Conference or Workshop Item
Copyright Holders: 2015 The Authors
Keywords: information retrieval; readability prediction; eye movements
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
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Item ID: 44133
Depositing User: Dawei Song
Date Deposited: 24 Aug 2015 09:56
Last Modified: 07 Dec 2018 22:55
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