A Fully Automatic Question-Answering System for Intelligent Search in E-Learning Documents
Ankush Mittal, Sumit Gupta, Praveen Kumar, Shrikant Kashyap, Indian Institute of Technology, Roorkee, India
International Journal on E-Learning Volume 4, Number 1, ISSN 1537-2456 Publisher: Association for the Advancement of Computing in Education (AACE), Waynesville, NC USA
E-learning is a novel method for presenting information to students for the purpose of education. Currently a sea of information is available in the form of power point slides, FAQ and e-books. However the potential of this large body remains unrealized due to lack of an effective information retrieval system. Current search engines are used only for web and return ranked list of documents. Such engines would not be effective searching tools for E-learning documents and it would be difficult for a user to find the intended answer. This paper introduces a fully automatic Question-Answering (QA) System that allows students to ask a question in common language and receive an answer quickly and succinctly, with sufficient context to validate answer. The system uses Natural language processing techniques to identify the semantic and syntactic structure of the question. It configures itself to a particular domain by automatically recognizing the entities from the course material. The Information Retrieval engine is used to extract answer passages using contextual information. A closed loop dialogue with the user leads to effective answer extraction through extensive passage analysis. Experimental results of the system are shown over the course material of Computer Networks.
Mittal, A., Gupta, S., Kumar, P. & Kashyap, S. (2005). A Fully Automatic Question-Answering System for Intelligent Search in E-Learning Documents. International Journal on E-Learning, 4(1), 149-166. Norfolk, VA: Association for the Advancement of Computing in Education (AACE).
© 2005 Association for the Advancement of Computing in Education (AACE)
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Dunwei Wen, John Cuzzola, Lorna Brown & Kinshuk, Athabasca University
The International Review of Research in Open and Distributed Learning Vol. 13, No. 5 (Nov 08, 2012) pp. 102–125
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