This paper investigates the determination of semantic similarity by the incorporation of structural semantic knowledge from a lexical database and the learning ability of neural networks. The lexical database is assumed to be organised in a hierarchical structure. The extracted lexical knowledge contains the relative location of the concerned words in the lexical hierarchy. The neural network then processes available lexical knowledge to provide semantic similarity for words. Experimental evaluation against a benchmark set of human similarity ratings demonstrates that the proposed method is effective in measuring semantic similarity between words.
|Number of pages||6|
|Publication status||Published - 2002|
|Name||LECTURE NOTES IN COMPUTER SCIENCE|
|Publisher||SPRINGER-VERLAG BERLIN, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY|
3rd International Conference on Intelligent Data Engineering and Automated Learning, MANCHESTER, ENGLAND, AUG 12-14, 2002