Generating natural language text in response to questions about database structure
Generating natural language text in response to questions about database structure
Correcting object-related misconceptions (natural language)
Correcting object-related misconceptions (natural language)
Discourse structures for text generation
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Providing a unified account of definite noun phrases in discourse
ACL '83 Proceedings of the 21st annual meeting on Association for Computational Linguistics
Modeling the user's plans and goals
Computational Linguistics - Special issue on user modeling
Tailoring object descriptions to a user's level of expertise
Computational Linguistics - Special issue on user modeling
The repair of speech act misunderstandings by abductive inference
Computational Linguistics
Integrating natural language components into graphical discourse
ANLC '92 Proceedings of the third conference on Applied natural language processing
A new strategy for providing definitions in task-oriented dialogues
COLING '88 Proceedings of the 12th conference on Computational linguistics - Volume 2
Computing pronoun antecedents in an English query system
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 2
Combining discourse strategies to generate descriptions to users along a naive/expert spectrum
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 2
A conversational model of multimodal interaction in information systems
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
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As a user interacts with a database or expert system, s/he may reveal a misconception about the objects modeled by the system. This paper discusses the ROMPER system for responding to such misconceptions in a domain independent and context sensitive fashion. ROMPER reasons about possible sources of the misconception. It operates on a model of the user and generates a cooperative response based on this reasoning. The process is made context sensitive by augmenting the user model with a new notion of object perspective which highlights certain aspects of the user model due to previous discourse.