Using syntactic-based kernels for classifying temporal relations

Authors:
Seyed Abolghasem Mirroshandel;Gholamreza Ghassem-Sani;Mahdy Khayyamian
Affiliations:
Department of Computer Engineering, Sharif University of Technology, Tehran, Iran;Department of Computer Engineering, Sharif University of Technology, Tehran, Iran;Department of Computer Engineering, Sharif University of Technology, Tehran, Iran
Venue:
Journal of Computer Science and Technology - Special issue on natural language processing
Year:
2011

Citing 23
Cited 1

Towards a general theory of action and time

Artificial Intelligence
A training algorithm for optimal margin classifiers

COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
DIRT @SBT@discovery of inference rules from text

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Machine learning of temporal relations

ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A composite kernel to extract relations between entities with both flat and structured features

ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Discovering asymmetric entailment relations between verbs using selectional preferences

ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Acquisition of verb entailment from text

HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Acquiring inference rules with temporal constraints by using Japanese coordinated sentences and noun-verb co-occurrences

HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Timelines from Text: Identification of Syntactic Temporal Relations

ICSC '07 Proceedings of the International Conference on Semantic Computing
Finding event, temporal and causal structure in text: a machine learning approach

Finding event, temporal and causal structure in text: a machine learning approach
Learning semantic links from a corpus of parallel temporal and causal relations

HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Classifying temporal relations between events

ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Two-phased event relation acquisition: coupling the relation-oriented and argument-oriented approaches

COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Experiments with reasoning for temporal relations between events

COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Inducing temporal graphs

EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Jointly combining implicit constraints improves temporal ordering

EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Syntactic kernels for natural language learning: the semantic role labeling case

NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
Syntactic tree-based relation extraction using a generalization of Collins and Duffy convolution tree kernel

SRWS '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Student Research Workshop and Doctoral Consortium
CU-TMP: temporal relation classification using syntactic and semantic features

SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
WVALI: temporal relation identification by syntactico-semantic analysis

SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Learning sentence-internal temporal relations

Journal of Artificial Intelligence Research
TimeML-compliant text analysis for temporal reasoning

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Global path-based refinement of noisy graphs applied to verb semantics

IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing

Towards unsupervised learning of temporal relations between events

Journal of Artificial Intelligence Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

Temporal relation classification is one of contemporary demanding tasks of natural language processing. This task can be used in various applications such as question answering, summarization, and language specific information retrieval. In this paper, we propose an improved algorithm for classifying temporal relations, between events or between events and time, using support vector machines (SVM). Along with gold-standard corpus features, the proposed method aims at exploiting some useful automatically generated syntactic features to improve the accuracy of classification. Accordingly, a number of novel kernel functions are introduced and evaluated. Our evaluations clearly demonstrate that adding syntactic features results in a considerable improvement over the state-of-the-art method of classifying temporal relations.