Boosting variant recognition with light semantics
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Experiments with open-domain textual Question Answering
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Syntagmatic and paradigmatic representations of term variation
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Open-domain textual question answering techniques
Natural Language Engineering
Natural language question answering: the view from here
Natural Language Engineering
Selecting Answers to Questions from Web Documents by a Robust Validation Process
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Numeric Query Answering on the Web
International Journal on Semantic Web & Information Systems
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Answering precise questions requires applying Natural Language techniques in order to locate the answers inside retrieved documents. The QALC system, presented in this paper, participated to the Question Answering track of the TREC8 and TREC9 evaluations. QALC exploits an analysis of documents based on the search for multi-word terms and their variations. These indexes are used to select a minimal number of documents to be processed and to give indices when comparing question and sentence representations. This comparison also takes advantage of a question analysis module and recognition of numeric and named entities in the documents.