@inproceedings{5bdf5ccc028247fca42849ed8aa6b93b,
title = "A cluster-based classification approach to semantic role labeling",
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.",
keywords = "Classification, Clustering, Machine Learning, Natural Language Processing",
author = "Ozgencil, {Necati E.} and Nancy McCracken and Kishan Mehrotra",
year = "2008",
doi = "10.1007/978-3-540-69052-8_28",
language = "English (US)",
isbn = "354069045X",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "265--275",
booktitle = "New Frontiers in Applied Artificial Intelligence - 21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008, Proceedings",
note = "21st International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2008 ; Conference date: 18-06-2008 Through 20-06-2008",
}