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Authors: Ghulam Sarwar ; Colm O'Riordan and John Newell

Affiliation: National University of Ireland and Galway, Ireland

ISBN: 978-989-758-271-4

ISSN: 2184-3228

Keyword(s): Document Retrieval, Passage-based Document Retrieval, Passage Similarity Functions.

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: Several researchers have considered the use of passages within documents as useful units of representation as individual passages may capture accurately the topic of discourse in a document. In this work, each document is indexed as a series of unique passages. We explore and analyse a number of similarity measures which take into account the similarity at passage level with the aim of improving the quality of the answer set. We define a number of such passage level approaches and compare their performance. Mean average precision (MAP) and precision at k documents (P@k) are used as measures of the quality of the approaches. The results show that for the different test collections, the rank of a passage is a useful measure, and when used separately or in conjunction with the document score can give better results as compared to other passage or document level similarity approaches.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Sarwar, G.; O'Riordan, C. and Newell, J. (2017). Passage Level Evidence for Effective Document Level Retrieval.In Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, ISBN 978-989-758-271-4, pages 83-90. DOI: 10.5220/0006502800830090

@conference{kdir17,
author={Ghulam Sarwar. and Colm O'Riordan. and John Newell.},
title={Passage Level Evidence for Effective Document Level Retrieval},
booktitle={Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,},
year={2017},
pages={83-90},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006502800830090},
isbn={978-989-758-271-4},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR,
TI - Passage Level Evidence for Effective Document Level Retrieval
SN - 978-989-758-271-4
AU - Sarwar, G.
AU - O'Riordan, C.
AU - Newell, J.
PY - 2017
SP - 83
EP - 90
DO - 10.5220/0006502800830090

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