Customisable semantic analysis of texts

Authors:
Vivi Nastase;Stan Szpakowicz
Affiliations:
School of Information Technology and Engineering, University of Ottawa, Ottawa, Ontario, Canada;School of Information Technology and Engineering, University of Ottawa, Ottawa, Ontario, Canada
Venue:
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
Year:
2005

Citing 12
Cited 0

Forgetting Exceptions is Harmful in Language Learning

Machine Learning - Special issue on natural language learning
Representing roles and purpose

Proceedings of the 1st international conference on Knowledge capture
Automatic labeling of semantic roles

Computational Linguistics
Pattern Matching for Case Analysis: A Computational Definition of Closeness

ICCI '93 Proceedings of the Fifth International Conference on Computing and Information
Test-Driving TANKA: Evaluating a Semi-automatic System of Text Analysis for Knowledge Acquisition

AI '98 Proceedings of the 12th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
Discovering word senses from text

Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Semiautomatic recognition of semantic relationships in english technical texts

Semiautomatic recognition of semantic relationships in english technical texts
The Berkeley FrameNet Project

COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Concept discovery from text

COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
The descent of hierarchy, and selection in relational semantics

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Semantic interpretation of nominalizations

AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Building concept representations from reusable components

AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence

Quantified Score

Hi-index	0.01

Visualization

Abstract

Our customisable semantic analysis system implements a form of knowledge acquisition. It automatically extracts syntactic units from a text and semi-automatically assigns semantic information to pairs of units. The user can select the type of units of interest and the list of semantic relations to be assigned. The system examines parse trees to decide if there is interaction between concepts that underlie syntactic units. Memory-based learning proposes the most likely semantic relation for each new pair of syntactic units that may be semantically linked. We experiment with several configurations, varying the syntactic analyzer and the list of semantic relations.