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|Title:||A graph-based approach to commonsense concept extraction and semantic similarity detection||Authors:||Rajagopal, D.
Commonsense knowledge representation and reasoning
Natural language processing
|Issue Date:||2013||Citation:||Rajagopal, D., Cambria, E., Olsher, D., Kwok, K. (2013). A graph-based approach to commonsense concept extraction and semantic similarity detection. WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web : 565-570. ScholarBank@NUS Repository.||Abstract:||Commonsense knowledge representation and reasoning support a wide variety of potential applications in fields such as document auto-categorization, Web search enhancement, topic gisting, social process modeling, and concept-level opinion and sentiment analysis. Solutions to these problems, however, demand robust knowledge bases capable of supporting exible, nuanced reasoning. Populating such knowledge bases is highly time-consuming, making it necessary to develop techniques for deconstructing natural language texts into commonsense concepts. In this work, we propose an approach for effective multi-word commonsense expression extraction from unrestricted English text, in addition to a semantic similarity detection technique allowing additional matches to be found for specific concepts not already present in knowledge bases.||Source Title:||WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web||URI:||http://scholarbank.nus.edu.sg/handle/10635/116678||ISBN:||9781450320382|
|Appears in Collections:||Staff Publications|
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