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Authors: Alaa Mohasseb ; Mohamed Bader-El-Den and Mihaela Cocea

Affiliation: School of Computing, University of Portsmouth, Portsmouth and U.K.

Keyword(s): Information Retrieval, Question Classification, Factoid Questions, Grammatical Features, Machine Learning.

Abstract: The process of classifying questions in any question answering systems is the first step in retrieving accurate answers. Factoid questions are considered the most challenging type of question to classify. In this paper, a framework has been adapted for question categorization and classification. The framework consists of three main features which are, grammatical features, domain-specific features, and grammatical patterns. These features help in preserving and utilizing the structure of the questions. Machine learning algorithms were used for the classification process in which experimental results show that these features helped in achieving a good level of accuracy compared with the state-of-art approaches.

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Paper citation in several formats:
Mohasseb, A.; Bader-El-Den, M. and Cocea, M. (2019). Domain Specific Grammar based Classification for Factoid Questions. In Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-758-386-5; ISSN 2184-3252, SciTePress, pages 177-184. DOI: 10.5220/0007958601770184

@conference{webist19,
author={Alaa Mohasseb. and Mohamed Bader{-}El{-}Den. and Mihaela Cocea.},
title={Domain Specific Grammar based Classification for Factoid Questions},
booktitle={Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST},
year={2019},
pages={177-184},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007958601770184},
isbn={978-989-758-386-5},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Web Information Systems and Technologies - WEBIST
TI - Domain Specific Grammar based Classification for Factoid Questions
SN - 978-989-758-386-5
IS - 2184-3252
AU - Mohasseb, A.
AU - Bader-El-Den, M.
AU - Cocea, M.
PY - 2019
SP - 177
EP - 184
DO - 10.5220/0007958601770184
PB - SciTePress

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