Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/78154
Title: From semantic to emotional space in probabilistic sense sentiment analysis
Authors: Mohtarami, M.
Lan, M.
Tan, C.L. 
Issue Date: 2013
Citation: Mohtarami, M.,Lan, M.,Tan, C.L. (2013). From semantic to emotional space in probabilistic sense sentiment analysis. Proceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013 : 711-717. ScholarBank@NUS Repository.
Abstract: This paper proposes an effective approach to model the emotional space of words to infer their Sense Sentiment Similarity (SSS). SSS reflects the distance between the words regarding their senses and underlying sentiments. We propose a probabilistic approach that is built on a hidden emotional model in which the basic human emotions are considered as hidden. This leads to predict a vector of emotions for each sense of the words, and then to infer the sense sentiment similarity. The effectiveness of the proposed approach is investigated in two Natural Language Processing tasks: Indirect yes/no Question Answer Pairs Inference and Sentiment Orientation Prediction. Copyright © 2013, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Source Title: Proceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013
URI: http://scholarbank.nus.edu.sg/handle/10635/78154
ISBN: 9781577356158
Appears in Collections:Staff Publications

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