by Giannis Varelas, Epimenidis Voutsakis, Paraskevi Raftopoulou, Euripides Petrakis, Evangelos E. Milios
Abstract:
Semantic Similarity relates to computing the similarity be- tween concepts which are not lexicographically similar. We investigate approaches to computing semantic similarity by mapping terms (concepts) to an ontology and by examin- ing their relationships in that ontology. Some of the most popular semantic similarity methods are implemented and evaluated using WordNet as the underlying reference ontol- ogy. Building upon the idea of semantic similarity, a novel information retrieval method is also proposed. This method is capable of detecting similarities between documents con- taining semantically similar but not necessarily lexicograph- ically similar terms. The proposed method has been eval- uated in retrieval of images and documents on the Web. The experimental results demonstrated very promising per- formance improvements over state-of-the-art information re- trieval methods.
Reference:
Semantic similarity methods in wordNet and their application to information retrieval on the web (Giannis Varelas, Epimenidis Voutsakis, Paraskevi Raftopoulou, Euripides Petrakis, Evangelos E. Milios), In Proceedings of the seventh ACM international workshop on Web information and data management - WIDM'05, ACM Press, 2005.
Bibtex Entry:
@article{Varelas2005a,
abstract = {Semantic Similarity relates to computing the similarity be- tween concepts which are not lexicographically similar. We investigate approaches to computing semantic similarity by mapping terms (concepts) to an ontology and by examin- ing their relationships in that ontology. Some of the most popular semantic similarity methods are implemented and evaluated using WordNet as the underlying reference ontol- ogy. Building upon the idea of semantic similarity, a novel information retrieval method is also proposed. This method is capable of detecting similarities between documents con- taining semantically similar but not necessarily lexicograph- ically similar terms. The proposed method has been eval- uated in retrieval of images and documents on the Web. The experimental results demonstrated very promising per- formance improvements over state-of-the-art information re- trieval methods.},
address = {New York, New York, USA},
annote = {
From Duplicate 1 (
Semantic similarity methods in wordNet and their application to information retrieval on the web
- Varelas, Giannis; Voutsakis, Epimenidis; Raftopoulou, Paraskevi; Petrakis, Euripides; Milios, Evangelos E. )
And Duplicate 2 (
Semantic similarity methods in wordNet and their application to information retrieval on the web
- Varelas, Giannis; Voutsakis, Epimenidis; Raftopoulou, Paraskevi; Petrakis, Euripides; Milios, Evangelos E. )
And Duplicate 3 (
Semantic similarity methods in wordNet and their application to information retrieval on the web
- Varelas, Giannis; Voutsakis, Epimenidis; Raftopoulou, Paraskevi; Petrakis, Euripides; Milios, Evangelos E )
},
author = {Varelas, Giannis and Voutsakis, Epimenidis and Raftopoulou, Paraskevi and Petrakis, Euripides and Milios, Evangelos E.},
doi = {10.1145/1097047.1097051},
isbn = {1595931945},
journal = {Proceedings of the seventh ACM international workshop on Web information and data management - WIDM'05},
keywords = {SML-LIB-BIBLIO,information retrieval,lang:ENG,semantic similarity,wordnet,world},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
pages = {10},
publisher = {ACM Press},
title = {{Semantic similarity methods in wordNet and their application to information retrieval on the web}},
url = {http://portal.acm.org/citation.cfm?doid=1097047.1097051},
year = {2005}
}