Making large-scale support vector machine learning practical
Advances in kernel methods
Automatic labeling of semantic roles
Computational Linguistics
Kernel methods for relation extraction
The Journal of Machine Learning Research
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Fast methods for kernel-based text analysis
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Support Vector Learning for Semantic Argument Classification
Machine Learning
Use of deep linguistic features for the recognition and labeling of semantic arguments
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Using LTAG based features in parse reranking
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
The Proposition Bank: An Annotated Corpus of Semantic Roles
Computational Linguistics
A study on convolution kernels for shallow semantic parsing
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Dependency tree kernels for relation extraction
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Semantic role labeling using different syntactic views
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Joint learning improves semantic role labeling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Speeding up training with tree kernels for node relation labeling
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Exploring syntactic features for relation extraction using a convolution tree kernel
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Engineering of syntactic features for shallow semantic parsing
FeatureEng '05 Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing
Introduction to the CoNLL-2005 shared task: semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
A joint model for semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Generalized inference with multiple semantic role labeling systems
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Hierarchical semantic role labeling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Semantic role chunking combining complementary syntactic views
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Applying spelling error correction techniques for improving semantic role labelling
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Efficient convolution kernels for dependency and constituent syntactic trees
ECML'06 Proceedings of the 17th European conference on Machine Learning
Using a Hybrid Convolution Tree Kernel for Semantic Role Labeling
ACM Transactions on Asian Language Information Processing (TALIP)
Cross-Language Frame Semantics Transfer in Bilingual Corpora
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
Frame Detection over the Semantic Web
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Kernel-based relation extraction from investigative data
Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data
Efficient linearization of tree kernel functions
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
Re-ranking models for spoken language understanding
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Syntactic Structural Kernels for Natural Language Interfaces to Databases
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Shallow semantic parsing for spoken language understanding
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Kernel-Based Learning for Domain-Specific Relation Extraction
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
A Robust Geometric Model for Argument Classification
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Reverse engineering of tree kernel feature spaces
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Re-ranking models based-on small training data for spoken language understanding
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Convolution kernels on constituent, dependency and sequential structures for relation extraction
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
A study of convolution tree kernel with local alignment
GEMS '09 Proceedings of the Workshop on Geometrical Models of Natural Language Semantics
Tree kernel-based semantic relation extraction with rich syntactic and semantic information
Information Sciences: an International Journal
From information to knowledge: harvesting entities and relationships from web sources
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Convolution kernels for opinion holder extraction
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Towards open-domain Semantic Role Labeling
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Edit tree distance alignments for semantic role labelling
ACLstudent '10 Proceedings of the ACL 2010 Student Research Workshop
Semantic role labeling for open information extraction
FAM-LbR '10 Proceedings of the NAACL HLT 2010 First International Workshop on Formalisms and Methodology for Learning by Reading
On reverse feature engineering of syntactic tree kernels
CoNLL '10 Proceedings of the Fourteenth Conference on Computational Natural Language Learning
Large-scale support vector learning with structural kernels
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part III
Measuring tree similarity for natural language processing based information retrieval
NLDB'10 Proceedings of the Natural language processing and information systems, and 15th international conference on Applications of natural language to information systems
Kernel engineering for fast and easy design of natural language applications
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Kernel Engineering for Fast and Easy Design of Natural Language Applications
Evaluating FrameNet-style semantic parsing: the role of coverage gaps in FrameNet
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Journal of Computer Science and Technology
An analysis of open information extraction based on semantic role labeling
Proceedings of the sixth international conference on Knowledge capture
Social network extraction from texts: a thesis proposal
HLT-SS '11 Proceedings of the ACL 2011 Student Session
Unified Semantic Role Labeling for Verbal and Nominal Predicates in the Chinese Language
ACM Transactions on Asian Language Information Processing (TALIP)
ACM Transactions on Asian Language Information Processing (TALIP)
Using kernels on hierarchical graphs in automatic classification of designs
GbRPR'11 Proceedings of the 8th international conference on Graph-based representations in pattern recognition
Using sequence kernels to identify opinion entities in Urdu
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Latent topic models of surface syntactic information
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Structured learning for semantic role labeling
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Using syntactic and semantic structural kernels for classifying definition questions in Jeopardy!
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Structured lexical similarity via convolution kernels on dependency trees
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Hypotheses selection criteria in a reranking framework for spoken language understanding
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Semantic mapping between natural language questions and SQL queries via syntactic pairing
NLDB'09 Proceedings of the 14th international conference on Applications of Natural Language to Information Systems
Tree kernel-based protein-protein interaction extraction from biomedical literature
Journal of Biomedical Informatics
Efficient Graph Kernels for Textual Entailment Recognition
Fundamenta Informaticae - RCRA 2009 Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion
Native language detection with tree substitution grammars
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
Labeling by landscaping: classifying tokens in context by pruning and decorating trees
Proceedings of the 21st ACM international conference on Information and knowledge management
Evaluating the impact of syntax and semantics on emotion recognition from text
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
Framing image description as a ranking task: data, models and evaluation metrics
Journal of Artificial Intelligence Research
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The availability of large scale data sets of manually annotated predicate-argument structures has recently favored the use of machine learning approaches to the design of automated semantic role labeling (SRL) systems. The main research in this area relates to the design choices for feature representation and for effective decompositions of the task in different learning models. Regarding the former choice, structural properties of full syntactic parses are largely employed as they represent ways to encode different principles suggested by the linking theory between syntax and semantics. The latter choice relates to several learning schemes over global views of the parses. For example, re-ranking stages operating over alternative predicate-argument sequences of the same sentence have shown to be very effective. In this article, we propose several kernel functions to model parse tree properties in kernel-based machines, for example, perceptrons or support vector machines. In particular, we define different kinds of tree kernels as general approaches to feature engineering in SRL. Moreover, we extensively experiment with such kernels to investigate their contribution to individual stages of an SRL architecture both in isolation and in combination with other traditional manually coded features. The results for boundary recognition, classification, and re-ranking stages provide systematic evidence about the significant impact of tree kernels on the overall accuracy, especially when the amount of training data is small. As a conclusive result, tree kernels allow for a general and easily portable feature engineering method which is applicable to a large family of natural language processing tasks.