BASEBALL: an automatic question answerer
Readings in natural language processing
ANTLR: a predicated-LL(k) parser generator
Software—Practice & Experience
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Automated Question Answering: Review of the Main Approaches
ICITA '05 Proceedings of the Third International Conference on Information Technology and Applications (ICITA'05) Volume 2 - Volume 02
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
Semantic pattern learning through maximum entropy-based WSD technique
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Progress in natural language understanding: an application to lunar geology
AFIPS '73 Proceedings of the June 4-8, 1973, national computer conference and exposition
The benefits of the interaction between data warehouses and question answering
Proceedings of the 2010 EDBT/ICDT Workshops
Automated email answering by text pattern matching
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
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Question Answering (Q&A) systems, unlike other Information Retrieval (IR) systems, aim at providing directly the answer to the user, and not a list of documents in which the correct answer may be found. Our system is based on a data warehouse and provides composite answers made of a dataset and the corresponding chart visualizations. The question translation step is based on a new proposal for surface patterns that incorporate business semantic as well as domain-specific knowldege allowing a better coverage of questions.