Selecting predicate logic for knowledge representation by comparative study of knowledge representation schemes

In artificial intelligence, knowledge representation is a combination of data structures and interpretive procedures that leads to knowledgeable behavior. Therefore, it is required to investigate such knowledge representation technique in which knowledge can be easily and efficiently represented in computer. This research paper compares various knowledge representation techniques and proves that predicate logic is a more efficient and more accurate knowledge representation scheme. The algorithm in this paper splits the English text/sentences into phrases/constituents and then represents these in predicate logic. This algorithm also generates the original sentences from the representation in order to check the accuracy of representation. The algorithm has been tested on real text/sentences of English. The algorithm has achieved an accuracy of 80%. If the text is in simple discourse units, then the algorithm accurately represents it in predicate logic. The algorithm also accurately retrieves the original text/sentences from such representation.