Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICDMW.2011.106
Title: Isanette: A common and common sense knowledge base for opinion mining
Authors: Cambria, E. 
Song, Y.
Wang, H.
Hussain, A.
Keywords: Knowledge-based systems
Natural language processing
Opinion mining
Semantic networks
Issue Date: 2011
Source: Cambria, E.,Song, Y.,Wang, H.,Hussain, A. (2011). Isanette: A common and common sense knowledge base for opinion mining. Proceedings - IEEE International Conference on Data Mining, ICDM : 315-322. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDMW.2011.106
Abstract: The ability to understand natural language text is far from being emulated in machines. One of the main hurdles to overcome is that computers lack both the common and the common sense knowledge humans normally acquire during the formative years of their lives. If we want machines to really understand natural language, we need to provide them with this kind of knowledge rather than relying on the valence of keywords and word co-occurrence frequencies. In this work, we blend the largest existing taxonomy of common knowledge with a natural-language-based semantic network of common sense knowledge, and use multi-dimensionality reduction techniques on the resulting knowledge base for opinion mining and sentiment analysis. © 2011 IEEE.
Source Title: Proceedings - IEEE International Conference on Data Mining, ICDM
URI: http://scholarbank.nus.edu.sg/handle/10635/116747
ISBN: 9780769544090
ISSN: 15504786
DOI: 10.1109/ICDMW.2011.106
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

11
checked on Jan 17, 2018

Page view(s)

25
checked on Jan 15, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.