Knowledge Based Systems Rajendra Akerkar and Priti Sajja: A Book for Business Professionals Interest

Priti Srinivas Sajja has been working at the Post Graduate Department of Computer Science, Sardar Patel University, India since 1994 and presently holds the post of Professor. She specializes in Artificial Intelligence and Systems Analysis & Design especially in knowledge-based systems, soft computing and multi-agent systems. She is the author/co-author of Essence of Systems Analysis and Design: A Workbook Approach (Springer, 2017), Intelligent Techniques for Data Science (Springer, 2016); Intelligent Technologies for Web Applications (CRC, 2012) and Knowledge-Based Systems (J&B, 2009) published at Switzerland and USA, and four books published in India. She is supervising work of a few doctoral research scholars while seven candidates have completed their Ph.D research under her guidance. She has served as Principal Investigator of a major research project funded by the University Grants Commission, India.

Dr Priti Srinivas Sajja (b.1970) joined the faculty of the Department of Computer Science, Sardar Patel University, India in 1994 and is presently working as a Professor. She received her M.S. (1993) and Ph.D (2000) in Computer Science from the Sardar Patel University. Her research interests include knowledge-based systems, soft computing, multi-agent systems, and software engineering. She has 152 publications in books, book chapters, journals, and in the proceedings of national and international conferences out of which five publications have won best research paper awards. She is co-author of 'Knowledge-Based Systems' and 'Intelligent Technologies for Web Applications' published in the USA. She is supervising work of a few doctoral research scholars while six candidates have completed their Ph.D research under her guidance. She was Principal Investigator of a major research project funded by UGC, India. She is serving as a member on the editorial board of many international science journals and served as a program committee member for various international conferences.

Knowledge Based Systems Rajendra Akerkar and Priti Sajja}

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Priti Srinivas Sajja joined the faculty of the Department of Computer Science, Sardar Patel University, India in 1994 and presently works as an Associate Professor. She received her M.S. (1993) and Ph.D (2000) in Computer Science from the Sardar Patel University. Her research interests include knowledge-based systems, soft computing, multiagent systems, and software engineering. She has more than 100 publications in books, book chapters, journals, and in the proceedings of national and international conferences. Four of her publications have won best research paper awards. She is co-author of 'Knowledge-Based Systems'. She is supervising work of seven doctoral research students. She is Principal Investigator of a major research project funded by UGC, India. She is serving as a member in editorial board of many international science journals and served as program committee member for various international conferences.

A knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. The term is broad and refers to many different kinds of systems. The one common theme that unites all knowledge based systems is an attempt to represent knowledge explicitly and a reasoning system that allows it to derive new knowledge. Thus, a knowledge-based system has two distinguishing features: a knowledge base and an inference engine.

While the earliest knowledge-based systems were almost all expert systems, the same tools and architectures can and have since been used for a whole host of other types of systems. Virtually all expert systems are knowledge-based systems, but many knowledge-based systems are not expert systems.

The first knowledge-based systems were rule based expert systems. One of the most famous was Mycin, a program for medical diagnosis. These early expert systems represented facts about the world as simple assertions in a flat database, and used rules to reason about (and as a result add to) these assertions. Representing knowledge explicitly via rules had several advantages:

In addition to expert systems, other applications of knowledge-based systems include real-time process control,[6] intelligent tutoring systems,[7] and problem-solvers for specific domains such as protein structure analysis,[8] construction-site layout,[9] and computer system fault diagnosis.[10]

As knowledge-based systems became more complex, the techniques used to represent the knowledge base became more sophisticated and included logic, term-rewriting systems, conceptual graphs, and frames. Consider frames as an example. Rather than representing facts as assertions about data, the knowledge-base has become more structured. Frames can be thought of as representing world knowledge using analogous techniques to object-oriented programming, specifically the use of hierarchies of classes and subclasses, relations between classes, and behavior of objects. As the knowledge base became more structured, reasoning could occur both by independent rules, logical inference, and by interactions within the knowledge base itself. For example, procedures stored as daemons on objects could fire and could replicate the chaining behavior of rules.[11]

The most recent advancement of knowledge-based systems has been to adopt the technologies, especially a kind of logic called description logic, for the development of systems that use the internet. The internet often has to deal with complex, unstructured data that cannot be relied on to fit a specific data model. The technology of knowledge-based systems, and especially the ability to classify objects on demand, is ideal for such systems. The model for these kinds of knowledge-based Internet systems is known as the Semantic Web.[13] 2ff7e9595c