Title :
A new word sense similarity measure in wordnet
Author :
Sebti, Ali ; Barfroush, Ahmad Abodollahzadeh
Author_Institution :
Intell. Syst. Lab., Amirkabir Univ. of Technol., Tehran
Abstract :
Recognizing similarities between words is a basic element of computational linguistics and artificial intelligence applications. This paper presents a new approach for measuring semantic similarity between words via concepts. Our proposed measure is a hybrid system based on using a new Information content metric and edge counting-based tuning function. In proposed system, hierarchical structure is used to present information content instead of text corpus and our result will be improved by edge counting-based tuning function. The result of the system is evaluated against human similarity ratings demonstration and shows significant improvement in compare with traditional similarity measures.
Keywords :
artificial intelligence; computational linguistics; word processing; WordNet; artificial intelligence; computational linguistics; edge counting-based tuning function; hierarchical structure; information content metric; semantic similarity; word sense similarity measure; Artificial intelligence; Computational linguistics; Humans;
Conference_Titel :
Computer Science and Information Technology, 2008. IMCSIT 2008. International Multiconference on
Conference_Location :
Wisia
Print_ISBN :
978-83-60810-14-9
DOI :
10.1109/IMCSIT.2008.4747267