A Complex Network Approach for Evaluating Query Similarity Metrics

Rushed Kanawati

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Paper

A Complex Network Approach for Evaluating Query Similarity Metrics

In Proceedings of the 2nd International Workshop on Web Intelligence - Volume 0ICEIS, 32-41, 2013 , Angers, France

Author: Rushed Kanawati

Affiliation: University Paris Nord, France

Keyword(s): Query mining Query similarity, complex networks

Abstract: Query similarity is a core function in many information retrieval applications. A wide variety of similarity metrics can be defined, varying from simple term-based similarities to complex document (result) based similarities. However, no clear evaluation measurement of these different query similarity functions is yet provided. In this paper we show that effective similarity functions induce scale-free -similarity graphs.

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Paper citation in several formats:

Kanawati, R. (2013). A Complex Network Approach for Evaluating Query Similarity Metrics. In Proceedings of the 2nd International Workshop on Web Intelligence (ICEIS 2013) - WEBI; ISBN 978-989-8565-63-1, SciTePress, pages 32-41. DOI: 10.5220/0004603200320041

@conference{webi13,
author={Rushed Kanawati.},
title={A Complex Network Approach for Evaluating Query Similarity Metrics},
booktitle={Proceedings of the 2nd International Workshop on Web Intelligence (ICEIS 2013) - WEBI},
year={2013},
pages={32-41},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004603200320041},
isbn={978-989-8565-63-1},
}

TY - CONF

JO - Proceedings of the 2nd International Workshop on Web Intelligence (ICEIS 2013) - WEBI
TI - A Complex Network Approach for Evaluating Query Similarity Metrics
SN - 978-989-8565-63-1
AU - Kanawati, R.
PY - 2013
SP - 32
EP - 41
DO - 10.5220/0004603200320041
PB - SciTePress