Natural language understanding (2nd ed.)
Natural language understanding (2nd ed.)
An iterative design methodology for user-friendly natural language office information applications
ACM Transactions on Information Systems (TOIS)
Efficient string matching: an aid to bibliographic search
Communications of the ACM
ELIZA—a computer program for the study of natural language communication between man and machine
Communications of the ACM
A conversational agent as museum guide: design and evaluation of a real-world application
Lecture Notes in Computer Science
Speech and Language Processing (2nd Edition)
Speech and Language Processing (2nd Edition)
Statistical shallow semantic parsing despite little training data
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
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When developing a conversational agent, there is often an urgent need to have a prototype available in order to test the application with real users. A Wizard of Oz is a possibility, but sometimes the agent should be simply deployed in the environment where it will be used. Here, the agent should be able to capture as many interactions as possible and to understand how people react to failure. In this paper, we focus on the rapid development of a natural language understanding module by non experts. Our approach follows the learning paradigm and sees the process of understanding natural language as a classification problem. We test our module with a conversational agent that answers questions in the art domain. Moreover, we show how our approach can be used by a natural language interface to a cinema database.