Abstract
Background. Nowadays with the advent of technology and easy access to the “WWW”, there is a need for such systems that can give exact and precise answers to user’s queries. It leads to the requirement of the Question-Answering System. In this Paper, we are going to present “SN : CQA” (Semantic Network based Cognitive Question-Answering System).
Objective. The essential purpose of designing this system is to place such systems in the remote locations (but not limited to) where internet connectivity is not yet possible (Offering off-line experiential knowledge-base). Thus students, living in remote areas, can get the benefit of existing technologies and technical education.
Methodology. For practical implementation of the proposed architecture of “SN : CQA”, we have selected education domain (teaching “Basic Electrical Motor Concepts” to the novice users). Thus to achieve the required goal this paper proposes an architecture “SN : CQA”, which combines the power of (i) Semantic-Network, (ii) NLP, (iii) Agent’s behaviour modeling, and (iv) Cognitive behaviour modelling under one roof. “SN : CQA” tries to give best answers to user queries rather than the correct answers. This paper also emphasis on the requirement of experiential knowledge base (Teacher’s Experiences) rather than web mining based answer’s extraction.
Result. “SN : CQA” combines the power of several techniques under one architecture which leads to the better decision making while searching and answering the user’s queries.
Conclusion. Finally this paper concludes that for the construction of an effective QA system we should go for the architectural way of designing the system, which combines the powers of many individual techniques under one roof. This paper also emphasise on the importance of experimental knowledge base.
A. P. Prajapati and A. Chandiok are working in the field of artificial cognitive systems.
D. K. Chaturvedi is working in the field of softcomputing, cognitive and conscious systems.
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I would like to thank Dr. M. B. Lal Sahab and Dr. P. S. Satsangi Sahab for his continuous inspirations and blessings.
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Prajapati, A.P., Chandiok, A., Chaturvedi, D.K. (2019). Semantic Network Based Cognitive, NLP Powered Question Answering System for Teaching Electrical Motor Concepts. In: Akoglu, L., Ferrara, E., Deivamani, M., Baeza-Yates, R., Yogesh, P. (eds) Advances in Data Science. ICIIT 2018. Communications in Computer and Information Science, vol 941. Springer, Singapore. https://doi.org/10.1007/978-981-13-3582-2_8
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