Towards a Bio-inspired Approach to Match Heterogeneous Documents

Nourelhouda Yahi, Hacene Belhadef, Mathieu Roche, Amer Draa

2017

Abstract

Matching heterogeneous text documents coming from different sources means matching data extracted from these documents, generally structured in the form of vectors. The accuracy of matching directly depends on the right choice of the content of these vectors. That’s why we need to select the best features. In this paper, we present a new approach to select the minimum set of features that represents the semantics of a set of text documents, using a quantum inspired genetic algorithm. Among different Vs characterizing the big data we focus on ‘Variety’ criterion, therefore, we used three sets of different sources that are semantically similar to retrieve their best features which describe the semantics of the corpus. In the matching phase, our approach shows significant improvement compared with the classic ‘Bag-of-words’ approach.

Paper Citation

in Harvard Style

Yahi N., Belhadef H., Roche M. and Draa A. (2017). Towards a Bio-inspired Approach to Match Heterogeneous Documents . In Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-758-246-2, pages 276-283. DOI: 10.5220/0006294002760283

in Bibtex Style

@conference{webist17,
author={Nourelhouda Yahi and Hacene Belhadef and Mathieu Roche and Amer Draa},
title={Towards a Bio-inspired Approach to Match Heterogeneous Documents},
booktitle={Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2017},
pages={276-283},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006294002760283},
isbn={978-989-758-246-2},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 13th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - Towards a Bio-inspired Approach to Match Heterogeneous Documents
SN - 978-989-758-246-2
AU - Yahi N.
AU - Belhadef H.
AU - Roche M.
AU - Draa A.
PY - 2017
SP - 276
EP - 283
DO - 10.5220/0006294002760283