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Authors: Ghulam Sarwar and Stephen Bradshaw

Affiliation: Department of Information Technology, National University of Ireland, Galway and Ireland

ISBN: 978-989-758-330-8

Keyword(s): IR Theory and Practice, Query Expansion, Content Representation and Processing, Passage Level Retrieval and Evidence.

Abstract: This paper documents an approach that i) uses graphs to capture the semantic relatedness between terms in text and ii) augmenting queries with those terms deemed to be semantically related to the query terms. In building the graphs we use a relatively straightforward approach based on term locations; we investigate approaches that aid query improvement by capturing the semantic relatedness that is extracted at passage level as well as the complete document level. Semantic relatedness between is represented on a graph, where the terms are stored as nodes and the strength of their connection is recorded as an edge weight. In this fashion, we recorded the degree of connection between terms and use this to suggest possible additional words for improving the precision of a query. We compare the results of both approaches to a traditional approach and present a number of experiments at passage and document level. Our findings are that the approaches investigated achieve a competitive standa rd against a well known baseline. (More)

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Paper citation in several formats:
Sarwar, G. and Bradshaw, S. (2018). Investigating the Use of Semantic Relatedness at Document and Passage Level for Query Augmentation.In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-330-8, pages 237-244. DOI: 10.5220/0006935902370244

@conference{kdir18,
author={Ghulam Sarwar. and Stephen Bradshaw.},
title={Investigating the Use of Semantic Relatedness at Document and Passage Level for Query Augmentation},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2018},
pages={237-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006935902370244},
isbn={978-989-758-330-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - Investigating the Use of Semantic Relatedness at Document and Passage Level for Query Augmentation
SN - 978-989-758-330-8
AU - Sarwar, G.
AU - Bradshaw, S.
PY - 2018
SP - 237
EP - 244
DO - 10.5220/0006935902370244

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