Towards MORK: Model for Representing Knowledge

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S. Praveena Rachel Kamala 1,* S. Justus 1

1. School of Computer Science and Engineering, VIT University, Chennai, 600 127, India

* Corresponding author.


Received: 26 Oct. 2015 / Revised: 9 Dec. 2015 / Accepted: 13 Jan. 2016 / Published: 8 Mar. 2016

Index Terms

Knowledge Representation, Knowledge Retrieval, Conceptual Graph, Description Logics, Predicate Logic


Smart world needs intelligent system for effective and timely decision making. This is achieved only through a knowledge based system with functional knowledge representation units. In this paper, two models are proposed for representing knowledge. This process involves in getting the data and placing the information in the correct location. Logical notations are used for taking the clauses and graph is used for putting the entities. In Model one, the data is translated into logical statements using predicate logics, later the knowledge is stored in conceptual graph and retrieved. Whereas in Model two, the given information is translated using First Order Logic (FOL), by applying description logic concept rules are defined and as a result reasoning is done. Storage is done by using concept-relation graph. The main aims of our models are to have easy and simple access over the information. These models return the required exact answer, for the higher order query posted by the end user to the intelligent system.

Cite This Paper

S. Praveena Rachel Kamala, S. Justus, "Towards MORK: Model for Representing Knowledge", International Journal of Modern Education and Computer Science(IJMECS), Vol.8, No.3, pp.45-53, 2016. DOI:10.5815/ijmecs.2016.03.06


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