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Semantic classification of noun phrases using web counts and learning algorithms

Nulty, Paul (2007) Semantic classification of noun phrases using web counts and learning algorithms. In: Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop, 2007-01-01.

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Abstract

This paper investigates the use of machine learning algorithms to label modifier-noun compounds with a semantic relation. The attributes used as input to the learning algorithms are the web frequencies for phrases containing the modifier, noun, and a prepositional joining term. We compare and evaluate different algorithms and different joining phrases on Nastase and Szpakowicz’s (2003) dataset of 600 modifier-noun compounds. We find that by using a Support Vector Machine classifier we can obtain better performance on this dataset than a current state-of-the-art system; even with a relatively small set of prepositional joining terms.

Item Type: Conference or Workshop Item (Paper)
Official URL: http://www.aclweb.org/policies
Additional Information: © 2007 Association for Computational Linguistics
Divisions: Methodology
Subjects: C Auxiliary Sciences of History > C Auxiliary sciences of history (General)
Q Science > QA Mathematics > QA76 Computer software
JEL classification: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods and Programming > C61 - Optimization Techniques; Programming Models; Dynamic Analysis
Sets: Departments > Methodology
Date Deposited: 08 Jul 2014 16:06
Last Modified: 30 Jan 2019 21:19
URI: http://eprints.lse.ac.uk/id/eprint/57579

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