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Authors: Ghulam Sarwar and Stephen Bradshaw

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

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

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Symbolic Systems

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 stand ard 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 (IC3K 2018) - KDIR; ISBN 978-989-758-330-8; ISSN 2184-3228, SciTePress, 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 (IC3K 2018) - KDIR},
year={2018},
pages={237-244},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006935902370244},
isbn={978-989-758-330-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR
TI - Investigating the Use of Semantic Relatedness at Document and Passage Level for Query Augmentation
SN - 978-989-758-330-8
IS - 2184-3228
AU - Sarwar, G.
AU - Bradshaw, S.
PY - 2018
SP - 237
EP - 244
DO - 10.5220/0006935902370244
PB - SciTePress