User biased document language modelling

L. Azzopardi; M. Girolami; C. J. van Rijsbergen

doi:10.1145/1008992.1009111

User biased document language modelling

L. Azzopardi, M. Girolami, C. J. van Rijsbergen

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

Abstract

Capitalizing on the intuitive underlying assumptions of Language Modelling for Ad-Hoc Retrieval we present a novel approach that is capable of injecting the user's context of the document collection into the retrieval process. The preliminary findings from the evaluation undertaken suggest that improved IR performance is possible under certain circumstances. This motivates further investigation to determine the extent and significance of this improved performance.

Original language	English
Title of host publication	SIGIR '04 Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Place of Publication	New York, NY, USA
Pages	542-543
Number of pages	2
DOIs	https://doi.org/10.1145/1008992.1009111
Publication status	Published - 25 Jul 2004
Externally published	Yes

Publication series

Name	SIGIR '04
Publisher	ACM

Keywords

context
user biased
language model
information retrieval

Access to Document

10.1145/1008992.1009111

Cite this

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title = "User biased document language modelling",

abstract = "Capitalizing on the intuitive underlying assumptions of Language Modelling for Ad-Hoc Retrieval we present a novel approach that is capable of injecting the user's context of the document collection into the retrieval process. The preliminary findings from the evaluation undertaken suggest that improved IR performance is possible under certain circumstances. This motivates further investigation to determine the extent and significance of this improved performance.",

keywords = "context, user biased, language model, information retrieval",

author = "L. Azzopardi and M. Girolami and {van Rijsbergen}, {C. J.}",

year = "2004",

month = jul,

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AU - Azzopardi, L.

AU - Girolami, M.

AU - van Rijsbergen, C. J.

PY - 2004/7/25

Y1 - 2004/7/25

N2 - Capitalizing on the intuitive underlying assumptions of Language Modelling for Ad-Hoc Retrieval we present a novel approach that is capable of injecting the user's context of the document collection into the retrieval process. The preliminary findings from the evaluation undertaken suggest that improved IR performance is possible under certain circumstances. This motivates further investigation to determine the extent and significance of this improved performance.

AB - Capitalizing on the intuitive underlying assumptions of Language Modelling for Ad-Hoc Retrieval we present a novel approach that is capable of injecting the user's context of the document collection into the retrieval process. The preliminary findings from the evaluation undertaken suggest that improved IR performance is possible under certain circumstances. This motivates further investigation to determine the extent and significance of this improved performance.

KW - context

KW - user biased

KW - language model

KW - information retrieval

U2 - 10.1145/1008992.1009111

DO - 10.1145/1008992.1009111

M3 - Conference contribution book

SN - 1-58113-881-4

T3 - SIGIR '04

SP - 542

EP - 543

BT - SIGIR '04 Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

CY - New York, NY, USA

ER -

User biased document language modelling

Abstract

Publication series

Keywords

Access to Document

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Cite this