Domain specific grammar based classification for factoid questions

Alaa Mohasseb*, Mohamed Bader-El-Den, Mihaela Cocea

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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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.
Original languageEnglish
Title of host publicationProceedings of the 15th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, 2019
EditorsAlessandro Bozzon, Francisco Domínguez Mayo, Joaquim Filipe
PublisherSciTePress
Pages177-184
Number of pages8
ISBN (Print)9789897583865
DOIs
Publication statusPublished - 18 Sep 2019
Event15th International Conference on Web Information Systems and Technologies - Vienna University of Technology, Vienna, Austria
Duration: 18 Sep 201920 Sep 2019
Conference number: 15
http://www.webist.org/Home.aspx

Conference

Conference15th International Conference on Web Information Systems and Technologies
Abbreviated titleWEBIST
Country/TerritoryAustria
CityVienna
Period18/09/1920/09/19
Internet address

Keywords

  • information retrieval
  • question classification
  • machine learning
  • grammatical features

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