Title :
Domain Representation Using Possibility Theory: An Exploratory Study
Author :
Khoury, Richard ; Karray, Fakhreddine ; Kamel, Mohamed S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON
Abstract :
This study explores a new domain representation method for natural language processing based on an application of possibility theory. In our method, domain-specific information is extracted from natural language documents using a mathematical process based on Rieger´s notion of semantic distances, and represented in the form of possibility distributions. We implement the distributions in the context of a possibilistic domain classifier, which is trained using the SchoolNet corpus.
Keywords :
information retrieval; natural language processing; pattern classification; possibility theory; statistical distributions; text analysis; uncertainty handling; SchoolNet corpus; domain representation; domain-specific information; information extraction; mathematical process; natural language documents; natural language processing; possibilistic domain classifier; possibility distributions; possibility theory; semantic distances; “Fuzzy,” language models; natural language processing (NLP); probabilistic reasoning; text analysis; uncertainty;
Journal_Title :
Fuzzy Systems, IEEE Transactions on
DOI :
10.1109/TFUZZ.2008.2005011
