A cluster-based classification approach to semantic role labeling

Necati E. Ozgencil, Nancy McCracken, Kishan Mehrotra

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper, a new approach for multi-class classification problems is applied to the Semantic Role Labeling (SRL) problem, which is an important task for natural language processing systems to achieve better semantic understanding of text. The new approach applies to any classification problem with large feature sets. Data is partitioned using clusters on a subset of the features. A multi-label classifier is then trained individually on each cluster, using automatic feature selection to customize the larger feature set for the cluster. This algorithm is applied to the Semantic Role Labeling problem and achieves improvements in accuracy for both the argument identification classifier and the argument labeling classifier.

Original languageEnglish (US)
Title of host publicationNew Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings
Pages265-275
Number of pages11
DOIs
StatePublished - Aug 4 2008
Event21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008 - Wroclaw, Poland
Duration: Jun 18 2008Jun 20 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5027 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008
CountryPoland
CityWroclaw
Period6/18/086/20/08

Keywords

  • Classification
  • Clustering
  • Machine Learning
  • Natural Language Processing

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Ozgencil, N. E., McCracken, N., & Mehrotra, K. (2008). A cluster-based classification approach to semantic role labeling. In New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings (pp. 265-275). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5027 LNAI). https://doi.org/10.1007/978-3-540-69052-8_28