|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|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.|
|Series/Report no.:||Fall Symposium Series Technical Reports, FS-10-02|
|Conference Name:||2010 AAAI Fall Symposium|
|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)|
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