TY - GEN
T1 - SenticNet
T2 - 2010 AAAI Fall Symposium
AU - Cambria, Erik
AU - Speer, Robert
AU - Havasi, Catherine
AU - Hussain, Amir
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/79960150095
M3 - Conference contribution
AN - SCOPUS:79960150095
SN - 9781577354840
T3 - AAAI Fall Symposium - Technical Report
SP - 14
EP - 18
BT - Commonsense Knowledge - Papers from the AAAI Fall Symposium, Technical Report
PB - AI Access Foundation
Y2 - 11 November 2010 through 13 November 2010
ER -