Publishing Partner: Cambridge University Press CUP Extra Publisher Login
amazon logo
More Info

Personal Directory Information

Name: Marco  De Boni
Institution: Unilever Corporate Research
Email: click here to access email
State and/or Country: United Kingdom   
Linguistic Field(s): Applied Linguistics
Computational Linguistics
Text/Corpus Linguistics
Subject Language(s): English
Selected Publications: De Boni, M., and Manandhar, S., 'Implementing Clarification Dialogue in Open-Domain Question Answering', accepted for publication in the Journal for Natural Language Engineering, to appear in 2005.

De Boni, M. 'A relevance-based theoretical foundation for question answering.', PhD Thesis, Department of Computer Science, University of york, 2004.

De Boni, M., and Manandhar, S., 'An Analysis of Clarification Dialogue for Question Answering', in Proceedings of HLT-NAACL 2003, Edmonton, Canada, 2003.

De Boni, M., and Manandhar, S., 'The use of sentence similarity as a semantic relevance metric for QA', in Proceedings of the AAAI Symposium on New Directions in Question Answering, Stanford, 2003.[.pdf]

De Boni, M., Jara, J.L., Manandhar, S., 'The YorkQA prototype question answering system', to appear in Proceedings of the 11th Text Retrieval Conference (TREC-11), Gaithersburg, US, 2003.[.pdf]

De Boni, M., and Manandhar, S., 'Automated discovery of telic relations for WordNet', in Proceedings of the first International WordNet conference, India, 2002. [.pdf]

Alfonseca, E., De Boni, M., Jara, J.L., Manandhar, S., 'A prototype Question Answering system using syntactic and semantic information for answer retrieval', in Proceedings of the 10th Text Retrieval Conference (TREC-10), Gaithersburg, US, 2002. [.pdf]

De Boni, M., Grieson, A., Moore, D., Palmer-Brown, D.., 'Proposed enhancements to a debating system', Proceedings of the Workshop on Computational Dialectics, 14th European Conference in Artificial Intelligence, Berlin, 2000.
Dissertation Abstract: A Relevance-based Theoretical Foundation for Question Answering
Academic Paper Abstract: Implementing clarification dialogues in open domain question answering
Learning Effective and Engaging Strategies for Advice-Giving Human-Machine Dialogue

Add to Linguist Directory Update your entry