Knowledge Resource Development for Identifying Matching Image Descriptions

Alicia Sagae, Scott E. Fahlman

Abstract

Background knowledge resources contribute to the performance of many current systems for textual inference tasks (QA, textual entailment, summarization, retrieval, and others). However, it can be difficult to assess how additions to such a knowledge base will impact a system that relies on it. This paper describes the incremental, task-driven development of an ontology that provides features to a system that retrieves images based on their textual descriptions. We perform error analysis on a baseline system that uses lexical features only, then focus ontology development on reducing these errors against a development set. The resulting ontology contributes more to performance than domain-general resources like WordNet, even on a test set of previously unseen examples.

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Paper Citation


in Harvard Style

Sagae A. and Fahlman S. (2013). Knowledge Resource Development for Identifying Matching Image Descriptions . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013) ISBN 978-989-8565-81-5, pages 100-108. DOI: 10.5220/0004550601000108


in Bibtex Style

@conference{keod13,
author={Alicia Sagae and Scott E. Fahlman},
title={Knowledge Resource Development for Identifying Matching Image Descriptions},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)},
year={2013},
pages={100-108},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004550601000108},
isbn={978-989-8565-81-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)
TI - Knowledge Resource Development for Identifying Matching Image Descriptions
SN - 978-989-8565-81-5
AU - Sagae A.
AU - Fahlman S.
PY - 2013
SP - 100
EP - 108
DO - 10.5220/0004550601000108