Distributed Representations, Simple Recurrent Networks, And Grammatical Structure
Machine Learning - Connectionist approaches to language learning
Inductive learning algorithms and representations for text categorization
Proceedings of the seventh international conference on Information and knowledge management
Making large-scale support vector machine learning practical
Advances in kernel methods
Hybrid neural plausibility networks for news agents
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
An approach to the automatic design of multiple classifier systems
Pattern Recognition Letters - Special issue on machine learning and data mining in pattern recognition
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
A Theoretical Study on Six Classifier Fusion Strategies
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Information Retrieval
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the relationship between majority vote accuracy and dependency in multiple classifier systems
Pattern Recognition Letters
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Journal of Artificial Intelligence Research
The generalization error of the symmetric and scaled support vector machines
IEEE Transactions on Neural Networks
A Misclassification Reduction Approach for Automatic Call Routing
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Hybrid classifiers based on semantic data subspaces for two-level text categorization
International Journal of Hybrid Intelligent Systems
Automated detecting and classifying of sleep apnea syndrome based on genetic-SVM
International Journal of Hybrid Intelligent Systems
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In this paper we describe an approach for spoken language analysis for helpdesk call routing using a combination of simple recurrent networks and support vector machines. In particular we examine this approach for its potential in a difficult spoken language classification task based on recorded operator assistance telephone utterances. We explore simple recurrent networks and support vector machines using a large, unique telecommunication corpus of spontaneous spoken language. The main contribution of the paper is a combination of techniques in the domain of call routing. First, we find that simple recurrent networks perform better than support vector machines for this task. Second, we claim that the combination of simple recurrent networks and support vector machines provides slightly improved performance compared to the performance of either simple recurrent networks or support vector machines.