Detection of Semantic Relationships between Terms with a New Statistical Method

Nesrine Ksentini, Mohamed Tmar, Faïez Gargouri

2014

Abstract

Semantic relatedness between terms plays an important role in many applications, such as information retrieval, in order to disambiguate document content. This latter is generally studied among pairs of terms and is usually presented in a non-linear way. This paper presents a new statistical method for detecting relationships between terms called Least Square Mehod which defines these relations linear and between a set of terms. The evaluation of the proposed method has led to optimal results with low error rate and meaningful relationships. Experimental results show that the use of these relationships in query expansion process improves the retrieval results.

Paper Citation

in Harvard Style

Ksentini N., Tmar M. and Gargouri F. (2014). Detection of Semantic Relationships between Terms with a New Statistical Method . In Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST, ISBN 978-989-758-024-6, pages 340-343. DOI: 10.5220/0004960403400343

in Bibtex Style

@conference{webist14,
author={Nesrine Ksentini and Mohamed Tmar and Faïez Gargouri},
title={Detection of Semantic Relationships between Terms with a New Statistical Method},
booktitle={Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,},
year={2014},
pages={340-343},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004960403400343},
isbn={978-989-758-024-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,
TI - Detection of Semantic Relationships between Terms with a New Statistical Method
SN - 978-989-758-024-6
AU - Ksentini N.
AU - Tmar M.
AU - Gargouri F.
PY - 2014
SP - 340
EP - 343
DO - 10.5220/0004960403400343