Development and statistical validation of an ontology-based question answering system Online publication date: Sun, 09-Jul-2017
by G. Suresh Kumar; G. Zayaraz
International Journal of Computer Aided Engineering and Technology (IJCAET), Vol. 9, No. 3, 2017
Abstract: Question answering systems in general use external knowledge sources for extracting answers. Domain specific question answering systems require pre-constructed knowledge sources like domain ontology. A major challenge in knowledge-based question answering system development is building a huge knowledge base with the objective and correct factual knowledge in the preferred domain. The process of collecting useful knowledge from various sources and maintaining in a knowledge repository is a useful process for providing required answer on demand with greater accuracy and efficiency. In this paper an experimental framework has been proposed for concept-relational ontology-based question answering process. The question answering framework proposed in this paper includes two subsystems: 1) a dynamic concept relational ontology construction module, is capable to extract new concepts from the web and incorporate the extracted knowledge into the concept relational ontology knowledge base; 2) the answer extraction module formulates the query string from the natural language question according to the expected answer and retrieves the information from the ontology for answer formation. Furthermore, a novel statistical validation framework for evaluating the prototype implementation of the proposed question answering system is introduced.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Aided Engineering and Technology (IJCAET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com