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Author: Martin Emms

Affiliation: Trinity College, United Kingdom

Abstract: The application of tree-distance to clustering is considered. Previous work identified some parameters which favourably affect the use of tree-distance in question-answering tasks. Some evidence is given that the same parameters favourably affect the cluster quality. A potential application is in the creation of systems to carry out transformation of interrogative to indicative sentences, a first step in a question-answering system. It is argued that the clustering provides a means to navigate the space of parses assigned to large question sets. A tree-distance analogue of vector-space notion of centroid is proposed, which derives from a cluster a kind of pattern tree summarising the cluster.

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Paper citation in several formats:
Emms, M. (2006). Clustering by Tree Distance for Parse Tree Normalisation. In Proceedings of the 3rd International Workshop on Natural Language Understanding and Cognitive Science (ICEIS 2006) - NLUCS; ISBN 978-972-8865-50-4, SciTePress, pages 91-100. DOI: 10.5220/0002502400910100

@conference{nlucs06,
author={Martin Emms.},
title={Clustering by Tree Distance for Parse Tree Normalisation},
booktitle={Proceedings of the 3rd International Workshop on Natural Language Understanding and Cognitive Science (ICEIS 2006) - NLUCS},
year={2006},
pages={91-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002502400910100},
isbn={978-972-8865-50-4},
}

TY - CONF

JO - Proceedings of the 3rd International Workshop on Natural Language Understanding and Cognitive Science (ICEIS 2006) - NLUCS
TI - Clustering by Tree Distance for Parse Tree Normalisation
SN - 978-972-8865-50-4
AU - Emms, M.
PY - 2006
SP - 91
EP - 100
DO - 10.5220/0002502400910100
PB - SciTePress