Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/26397
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Cambria, Erik
Speer, Robert
Havasi, Catherine
Hussain, Amir
Contact Email: amir.hussain@stir.ac.uk
Title: SenticNet: A publicly available semantic resource for opinion mining
Citation: Cambria E, Speer R, Havasi C & Hussain A (2010) SenticNet: A publicly available semantic resource for opinion mining In: Commonsense Knowledge: Papers from the AAAI Fall Symposium, Menlo Park, CA, USA: AAAI Press. 2010 AAAI Fall Symposium, 11.11.2010 - 13.11.2010, Arlington, VA, USA, pp. 14-18.
Issue Date: 2010
Series/Report no.: Fall Symposium Series Technical Reports, FS-10-02
Conference Name: 2010 AAAI Fall Symposium
Conference Dates: 2010-11-11T00:00:00Z
Conference Location: Arlington, VA, USA
Abstract: Today millions of web-users express their opinions about many topics through blogs, wikis, fora, chats and social networks. For sectors such as e-commerce and e-tourism, it is very useful to automatically analyze the huge amount of social information available on the Web, but the extremely unstructured nature of these contents makes it a difficult task. SenticNet is a publicly available resource for opinion mining built exploiting AI and Semantic Web techniques. It uses dimensionality reduction to infer the polarity of common sense concepts and hence provide a public resource for mining opinions from natural language text at a semantic, rather than just syntactic, level.
Status: Publisher version (final published refereed version)
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
URL: http://www.aaai.org/Press/Reports/Symposia/Fall/fall-reports.php

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