TMRF e-Book Advanced Knowledge Based Systems: Model, Applications & Research (Eds. Sajja & Akerkar), Vol. 1, pp 1 – 11, 2010

Chapter 1

Knowledge-Based Systems for Development
Priti Srinivas Sajja, Rajendra Akerkar
INTRODUCTION Human brain can store several thousand folds of world’s knowledge. Still it is said that human brain is not fully utilized. Advances in human knowledge are tied directly to the ability to analyze to form information, process it into knowledge and communicate it to others. The human brain has approximately 1011 nerve cells called biological neurons. It is probably the most complex and least understood part of the human body. It is continuously thinking in declarative and procedural way for problem solving. But till today it is a mystery that how does the human mind work. This new millennium brought us an opportunity to attack all such questions with the help of new knowledge, new tools and new resources. Development of systems that make use of knowledge, wisdom and intelligence is a step towards meeting this challenge. The ability of the intelligent systems to capture and redistribute expertise has significant implications on development of a nation, commodity or population. Such systems allow documentation of one or more expert knowledge and utilize the knowledge for problem solving in cost effective way. It allows for, in a controlled manner, the import of expertise in various areas that the nation lacks, the export of knowledge relating to domestic areas of expertise, and the duplication and redistribution of scarce knowledge in a cost effective manner (Darek and Jain 1991). Thus areas of expertise that the selected domain/region/nation is deficient in or possesses exclusively are potential candidates of the knowledge-based systems. Though synthesized information is a key element for success, in many businesses it is a missing piece. A significant amount of Gross National Product (GNP) is invested in transferring knowledge through education and training. The AI systems effectively distribute the scarce resources for the development process. The Knowledge-Based Systems (KBS), which are a step towards an intelligent system, can be justified when a few individuals have the majority of the knowledge. DIKW CHAIN Data, information, knowledge and wisdom are major elements of human thinking and reasoning process. There are distinctive differences between data, information, knowledge and wisdom. Data concern with observation and raw facts. They are useless without an additional processing viz. comparing, inferring, filtering etc. The processed data is known as information. We may conclude that knowledge is a result of processes like synthesis, filtration, comparison and analysis of available information to generate meaningful outcome. Over the time, the experience, judgment, values, laws etc. are to be added to have the wisdom. This is known as Data-Information-Knowledge-Wisdom

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Advanced Knowledge-Based Systems: Models, Applications and Research

(DIKW) chain. This chain is also known as data pyramid. These entities can be arranged as shown in Figure 1.

Volume

Intelligence Wisdom (experience)

Complexity & Sophistication

Knowledge (synthesis)

Information (analysis) Data

Figure 1: DIKW Chain

Knowledge can be classified in many different ways. Tacit knowledge, explicit knowledge, factual knowledge, procedural knowledge, commonsense knowledge, domain knowledge, meta knowledge, etc. Table 1 briefly introduces various types of knowledge. Knowledge Type Domain knowledge Description Domain knowledge is valid knowledge for a specified domain. Specialists and experts develop their own domain knowledge and use it for problem solving. Meta knowledge can be defined as knowledge about knowledge. Common sense knowledge is a general purpose knowledge expected to be present in every normal human being. Common-sense ideas tend to relate to events within human experience. Heuristic is a