Making large-scale support vector machine learning practical
Advances in kernel methods
An Evaluation of Statistical Approaches to Text Categorization
Information Retrieval
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Text classification using string kernels
The Journal of Machine Learning Research
Kernel methods for relation extraction
The Journal of Machine Learning Research
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Dependency tree kernels for relation extraction
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Corpus-based induction of syntactic structure: models of dependency and constituency
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
A shortest path dependency kernel for relation extraction
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Shallow semantics for relation extraction
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Composite kernels for relation extraction
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
A logic-based approach to relation extraction from texts
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Efficient convolution kernels for dependency and constituent syntactic trees
ECML'06 Proceedings of the 17th European conference on Machine Learning
Semi-supervised abstraction-augmented string kernel for multi-level bio-relation extraction
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
A logic-based approach to relation extraction from texts
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
A dependency treebank of Urdu and its evaluation
LAW VI '12 Proceedings of the Sixth Linguistic Annotation Workshop
Future trends in business analytics and optimization
Intelligent Data Analysis
A structural approach to extracting Chinese position relations from web pages
Journal of Web Engineering
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The automatic extraction of relations from unstructured natural text is challenging but offers practical solutions for many problems like automatic text understanding and semantic retrieval. Relation extraction can be formulated as a classification problem using support vector machines and kernels for structured data that may include parse trees to account for syntactic structure. In this paper we present new tree kernels over dependency parse trees automatically generated from natural language text. Experiments on a public benchmark data set show that our kernels with richer structural features significantly outperform all published approaches for kernel-based relation extraction from dependency trees. In addition we optimize kernel computations to improve the actual runtime compared to previous solutions.