@article{Bandar2003,
abstract = {Semantic similarity between words is becoming a generic problem for many applications of computational linguistics and artificial intelligence. This paper explores the determination of semantic similarity by a number of information sources, which consist of structural semantic information from a lexical taxonomy and information content from a corpus. To investigate how information sources could be used effectively, a variety of strategies for using various possible information sources are implemented. A new measure is then proposed which combines information sources nonlinearly. Experimental evaluation against a benchmark set of human similarity ratings demonstrates that the proposed measure significantly outperforms traditional similarity measures.},
author = {Li, Yuhua and Bandar, Zuhair A. and McLean, David},
doi = {10.1109/TKDE.2003.1209005},
issn = {1041-4347},
journal = {IEEE Transactions on Knowledge and Data Engineering},
keywords = {SML-LIB-BIBLIO,Semantic Similarity,Semantic similarity,corpus statistics.,information content,lang:ENG,lexical database},
mendeley-tags = {SML-LIB-BIBLIO,Semantic Similarity,lang:ENG},
month = jul,
number = {4},
pages = {871--882},
title = {{An approach for measuring semantic similarity between words using multiple information sources}},
url = {http://portal.acm.org/citation.cfm?id=1435677.858972},
volume = {15},
year = {2003}
}