T. R. Gopalakrishnan Nair

Work place: Saudi Aramco Endowed Chair, Technology and Information Management, PMU KSA

E-mail: trgnair@yahoo.com

Website:

Research Interests: Computational Engineering, Engineering

Biography

T.R. Gopalakrishnan Nair holds an M.Tech from IISc, Bangalore and Ph.D. in Computer Science.

Currently, he is the Saudi Aramco Endowed Chair, ARAMCO Endowed Chair – Technology, PMU, KSA Advanced Networking Research Group, and VP, Research, Research and Industry Incubation Center (RIIC), Dayananda Sagar Institutions, Bangalore, India. He has three decades of experience in computer science and engineering through research, industry and education. He has published several papers and holds patents in multi domains.

He is a Fellow of IE, senior member of IEEE & ACM and a member of AAAS. He is winner of PARAM Award for technology innovation. (www.trgnair.org).

Author Articles
Evolution of Knowledge Representation and Retrieval Techniques

By Meenakshi Malhotra T. R. Gopalakrishnan Nair

DOI: https://doi.org/10.5815/ijisa.2015.07.03, Pub. Date: 8 Jun. 2015

Existing knowledge systems incorporate knowledge retrieval techniques that represent knowledge as rules, facts or a hierarchical classification of objects. Knowledge representation techniques govern validity and precision of knowledge retrieved. There is a vital need to bring intelligence as part of knowledge retrieval techniques to improve existing knowledge systems. Researchers have been putting tremendous efforts to develop knowledge-based system that can support functionalities of the human brain. The intention of this paper is to provide a reference for further research into the field of knowledge representation to provide improved techniques for knowledge retrieval. This review paper attempts to provide a broad overview of early knowledge representation and retrieval techniques along with discussion on prime challenges and issues faced by those systems. Also, state-of-the-art technique is discussed to gather advantages and the constraints leading to further research work. Finally, an emerging knowledge system that deals with constraints of existing knowledge systems and incorporates intelligence at nodes, as well as links, is proposed.

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