Multilingual Question Classification based on surface text features

Authors:
E. Bisbal;D. Tomás;L. Moreno;J. L. Vicedo;A. Suárez
Affiliations:
DSIC, Technical University of Valencia (Spain);DLSI, University of Alicante (Spain);DSIC, Technical University of Valencia (Spain);DLSI, University of Alicante (Spain);DLSI, University of Alicante (Spain)
Venue:
Proceedings of the 2005 conference on Artificial Intelligence Research and Development
Year:
2005

Citing 14
Cited 0

Instance-Based Learning Algorithms

Machine Learning
A training algorithm for optimal margin classifiers

COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Support-Vector Networks

Machine Learning
A maximum entropy approach to natural language processing

Computational Linguistics
Lazy learning

Lazy learning
Fast training of support vector machines using sequential minimal optimization

Advances in kernel methods
Data mining: practical machine learning tools and techniques with Java implementations

Data mining: practical machine learning tools and techniques with Java implementations
Performance issues and error analysis in an open-domain question answering system

ACM Transactions on Information Systems (TOIS)
Maximum entropy models for natural language ambiguity resolution

Maximum entropy models for natural language ambiguity resolution
A maximum entropy-based word sense disambiguation system

COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Learning question classifiers

COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Question classification with support vector machines and error correcting codes

NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Adaptive language modeling using the maximum entropy principle

HLT '93 Proceedings of the workshop on Human Language Technology
Parsing and question classification for question answering

ODQA '01 Proceedings of the workshop on Open-domain question answering - Volume 12

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a multilingual approach to Question Classification based on machine learning, using language independent features. This way we obtain a system flexible and easily adaptable to new languages. Using a parallel corpus in English and Spanish, we test the performance of the system with three different techniques: Support Vector Machines,Memory-based Learning and Maximum Entropy.