Improving sentence retrieval with an importance prior

Leif Azzopardi; Ronald T. Fernández; David E. Losada

doi:10.1145/1835449.1835612

Improving sentence retrieval with an importance prior

Leif Azzopardi, Ronald T. Fernández, David E. Losada

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

Abstract

The retrieval of sentences is a core task within Information Retrieval. In this poster we employ a Language Model that incorporates a prior which encodes the importance of sentences within the retrieval model. Then, in a set of comprehensive experiments using the TREC Novelty Tracks, we show that including this prior substantially improves retrieval effectiveness, and significantly outperforms the current state of the art in sentence retrieval.

Original language	English
Title of host publication	SIGIR '10 Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of Publication	New York, NY, USA
Pages	779-780
Number of pages	2
DOIs	https://doi.org/10.1145/1835449.1835612
Publication status	Published - 19 Jul 2010
Externally published	Yes

Keywords

language model
sentence retrieval

Access to Document

10.1145/1835449.1835612

Cite this

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title = "Improving sentence retrieval with an importance prior",

abstract = "The retrieval of sentences is a core task within Information Retrieval. In this poster we employ a Language Model that incorporates a prior which encodes the importance of sentences within the retrieval model. Then, in a set of comprehensive experiments using the TREC Novelty Tracks, we show that including this prior substantially improves retrieval effectiveness, and significantly outperforms the current state of the art in sentence retrieval.",

keywords = "language model, sentence retrieval",

author = "Leif Azzopardi and Fern{\'a}ndez, {Ronald T.} and Losada, {David E.}",

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AU - Fernández, Ronald T.

AU - Losada, David E.

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N2 - The retrieval of sentences is a core task within Information Retrieval. In this poster we employ a Language Model that incorporates a prior which encodes the importance of sentences within the retrieval model. Then, in a set of comprehensive experiments using the TREC Novelty Tracks, we show that including this prior substantially improves retrieval effectiveness, and significantly outperforms the current state of the art in sentence retrieval.

AB - The retrieval of sentences is a core task within Information Retrieval. In this poster we employ a Language Model that incorporates a prior which encodes the importance of sentences within the retrieval model. Then, in a set of comprehensive experiments using the TREC Novelty Tracks, we show that including this prior substantially improves retrieval effectiveness, and significantly outperforms the current state of the art in sentence retrieval.

KW - language model

KW - sentence retrieval

U2 - 10.1145/1835449.1835612

DO - 10.1145/1835449.1835612

M3 - Conference contribution book

SN - 978-1-4503-0153-4

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EP - 780

BT - SIGIR '10 Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval

CY - New York, NY, USA

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