Toward a Neural Aggregated Search Model for Semi-structured Documents

F. Z. Bessai-Mechmache

2013

Abstract

One of the main issues in aggregated search for XML documents is to select the relevant elements for information need. Our objective is to gather in same aggregate relevant elements that can belong to different parts of XML document and that are semantically related. To do this, we propose a neural aggregated search model using Kohonen self-organizing maps. Kohonen self-organizing map lets classification of XML elements producing density map that form the foundations of our model.

Paper Citation

in Harvard Style

Bessai-Mechmache F. (2013). Toward a Neural Aggregated Search Model for Semi-structured Documents . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013) ISBN 978-989-8565-75-4, pages 91-95. DOI: 10.5220/0004538400910095

in Bibtex Style

@conference{kdir13,
author={F. Z. Bessai-Mechmache},
title={Toward a Neural Aggregated Search Model for Semi-structured Documents},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)},
year={2013},
pages={91-95},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004538400910095},
isbn={978-989-8565-75-4},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)
TI - Toward a Neural Aggregated Search Model for Semi-structured Documents
SN - 978-989-8565-75-4
AU - Bessai-Mechmache F.
PY - 2013
SP - 91
EP - 95
DO - 10.5220/0004538400910095