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*DISCRIMINANT ANALYSIS (1)
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1
Discriminative Slot Detection Using Kernel Methods
Zhao, Shubin
;
Meyers, Adam
;
Grishman, Ralph
In: DTIC (2004)
Abstract:
Most traditional information extraction approaches are generative models that assume events exist in text in certain patterns and these patterns can be regenerated in various ways. These assumptions limited the syntactic clues being considered for finding an event and confined these approaches to a particular syntactic level. This paper presents a discriminative framework based on kernel SVMs that takes into account different levels of syntactic information and automatically identifies the appropriate clues. Kernels are used to represent certain levels of syntactic structure and can be combined in principled ways as input for an SVM. We will show that by combining a low level sequence kernel with a high level kernel on a GLARF dependency graph, the new approach outperformed a good rule-based system on slot filler detection for MUC-6. ; Presented at the International Conference on Computational Linguistics (20th), held in Geneva Switzerland on 23-27 August, 2004. Pub. in the Proceedings of the International Conference on Computational Linguistics (20th), p757-763, 2004. Sponsored in part by DARPA and NSF grant ITS-0325657.
Keyword:
*DISCRIMINANT ANALYSIS
;
*DISCRIMINATIVE SLOT DETECTION
;
*INFORMATION RETRIEVAL
;
*KERNEL FUNCTIONS
;
*MATHEMATICAL MODELS
;
*RULE BASED SYSTEMS
;
Cybernetics
;
DISCRIMINATIVE CLASSIFIERS
;
EOD(EVENT OCCURRENCE DETECTION)
;
GLARF(GRAMMATICAL AND LOGICAL ARGUMENT REGULARIZATION FRAMEWORK)
;
GRAPHS
;
IE(INFORMATION EXTRACTION)
;
Information Science
;
Linguistics
;
MESSAGE UNDERSTANDING
;
NES(NAMED ENTITIES)
;
PATTERN RECOGNITION
;
SEQUENCES
;
SFD(SLOT FILLER DETECTION)
;
SVM(SUPPORT VECTOR MACHINE)
;
SYMPOSIA
;
SYNTAX
;
TEXT PROCESSING
URL:
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA460647
http://www.dtic.mil/docs/citations/ADA460647
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