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Exploring fact‐focused relevance and novelty detection

Exploring fact‐focused relevance and novelty detection Purpose – Automated sentence‐level relevance and novelty detection would be of direct benefit to many information retrieval systems. However, the low level of agreement between human judges performing the task is an issue of concern. In previous approaches, annotators were asked to identify sentences in a document set that are relevant to a given topic, and then to eliminate sentences that do not provide novel information. This paper aims to explore a new approach in which relevance and novelty judgments are made within the context of specific, factual information needs, rather than with respect to a broad topic. Design/methodology/approach – An experiment is conducted in which annotators perform the novelty detection task in both the topic‐focused and fact‐focused settings. Findings – Higher levels of agreement between judges are found on the task of identifying relevant sentences in the fact‐focused approach. However, the new approach does not improve agreement on novelty judgments. Originality/value – The analysis confirms the intuition that making sentence‐level relevance judgments is likely to be the more difficult of the two tasks in the novelty detection framework. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Documentation Emerald Publishing

Exploring fact‐focused relevance and novelty detection

Journal of Documentation , Volume 64 (4): 15 – Jul 25, 2008

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References (39)

Publisher
Emerald Publishing
Copyright
Copyright © 2008 Emerald Group Publishing Limited. All rights reserved.
ISSN
0022-0418
DOI
10.1108/00220410810884057
Publisher site
See Article on Publisher Site

Abstract

Purpose – Automated sentence‐level relevance and novelty detection would be of direct benefit to many information retrieval systems. However, the low level of agreement between human judges performing the task is an issue of concern. In previous approaches, annotators were asked to identify sentences in a document set that are relevant to a given topic, and then to eliminate sentences that do not provide novel information. This paper aims to explore a new approach in which relevance and novelty judgments are made within the context of specific, factual information needs, rather than with respect to a broad topic. Design/methodology/approach – An experiment is conducted in which annotators perform the novelty detection task in both the topic‐focused and fact‐focused settings. Findings – Higher levels of agreement between judges are found on the task of identifying relevant sentences in the fact‐focused approach. However, the new approach does not improve agreement on novelty judgments. Originality/value – The analysis confirms the intuition that making sentence‐level relevance judgments is likely to be the more difficult of the two tasks in the novelty detection framework.

Journal

Journal of DocumentationEmerald Publishing

Published: Jul 25, 2008

Keywords: Information retrieval; Text retrieval; Information searches; Semantics

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