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Towards MORK: Model for Representing Knowledge
Author(s) -
S. Praveena Rachel Kamala,
S. Justus
Publication year - 2016
Publication title -
international journal of modern education and computer science
Language(s) - English
Resource type - Journals
eISSN - 2075-017X
pISSN - 2075-0161
DOI - 10.5815/ijmecs.2016.03.06
Subject(s) - computer science , conceptual graph , predicate (mathematical logic) , knowledge representation and reasoning , first order logic , graph , notation , relation (database) , theoretical computer science , artificial intelligence , data mining , programming language , arithmetic , mathematics
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.

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