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СКАЧАТЬ Knowledge

      Knowledge is characterized as abilities, (i) which the person gains in terms of practice or learning; theoretical or practical knowledge of a subject; (ii) what is known inside or as a whole; facts and information; or (iii) knowing or acquainted with the experience of life or situation. This knowledge is defined accordingly. The retrieval of information requires complex cognitive processes including memory, understanding, connectivity, association, and reasoning. Knowledge of a subject and its capacity for usage for a specific purpose are also used to suggest trustworthy comprehension. Information may be divided into two forms of knowledge: tacit and clear. Tacit knowledge is the awareness that people have and yet cannot get. Tacit knowledge is more relevant since it gives people, locations, feelings, and memories a framework. Efficient tacit information transfer typically requires intensive intimate correspondence and trust. The tacit understanding is not easily shared. Still, consciousness comprises patterns and culture that we still cannot comprehend. On the other hand, information, which is easy to articulate, is called explicit knowledge. Coding or codification is the tool used to translate tacit facts into specific details. The awareness expressed, codified, and stored in such media is explicitly facts. Explicit information. The most common simple knowledge sources are guides, manuals, and protocols. Audio-visual awareness may also be an example of overt intelligence, which is based on the externalization of human skills, motivations, and knowledge.

      1.2.2 Knowledge Engineering

Edward Feigenbaum and Pamela McCorduck created Knowledge Engineering in 1983: To address difficult issues that typically need a great deal of human experience in the fields of engineering, knowledge engineering needs the integration of information of computer systems. In engineering, design information is an essential aspect. If the information is collected and held in the knowledge base, important cost and output gains may be accomplished. In a range of fields, information base content may be used as to reuse information in other ways for diverse goals, to employ knowledge to create smart systems capable of carrying out complicated design work. We shall disseminate knowledge to other individuals within an organization. While the advantages of information capture and usage are obvious, it has long been known in the AI world that knowledge is challenging to access from specialists. Second, the specialists do not remember and describe “tacit knowledge” effectively, and this operates subconsciously and, where it is not impossible, is difficult to overcome the problems arising from several subject matters that they learn. To elaborate, they have to know what it is called. Third, there are various prospects and points of view which include aggregation to provide a coherent view. Last, professionals create abstract concepts and shortcuts for which they cannot communicate. The area of information technology was created some 25 years ago to address such problems, and the role of the knowledge engineer was born. Since then, computer engineers have developed a variety of principles, methods, and tools that have improved the acquisition, use, and implementation of knowledge considerably.

1.3 Knowledge Engineering as a Modelling Process

There is also a consensus that the KBS construction approach may be used as a modeling operation. It is not intended to construct a cognitively appropriate model, but to build a model that offers similar results for problem-solving problems in the area of concern as seen in Figure 1.2.

Figure 1.2 Knowledge as modelling process.

Building a KBS requires building a programming model to acquire problem-solving capabilities like those of a domain specialist. This material is not directly available; therefore, it needs to be created and arranged.

1.4 Tools

      Intelligence engineers make the more efficient and less bogus use of dedicated computational tools for the acquisition, simulation, and handling of intelligence. PC PACK is a versatile compilation of this programmed, commercially available as a package of knowledge technology tools that are designed to be tested on a wide range of projects. The aim is to consider the key characteristics of the domain. The method simulates how anyone should label a text page with different colors such as green for suggestions and yellow for attributes. The labeled text would immediately be placed in the PCPACK database to be applied to all other resources when the user has highlighted a document. The MOKA and Popular KADS Methodologies are supported by the CFPACK. It is also fully compliant with information engineering approaches and techniques. The CFPACK is a software suite that includes the following

      1 (i) Protocol tool: It enables the discovery, recognition, and definition of interview transcripts, conclusions, and documentation that may be included in the knowledge base.

      2 (ii) Ladder Tool: This allows hierarchies of knowledge elements such as meanings, features, procedures, and specifications to be developed.

      3 (iii) Chart Tool: This allows users to build mobile networks of connections between data elements, such as process maps, maps of ideas, and cutting-edge diagrams.

      4 (iv) Matrix Tool: This allows grids that show the connection and attributes of the elements to be developed and edited.

      5 (v) Annotation tools: This facilitates the creation of sophisticated HTML annotations, with links to other sites and other knowledge templates automatically generated in the CFPACK.

      6 (vi) Tool publisher: This allows the creation from a knowledge base of a website or some other information resource using a model-driven approach to optimize re-usability. MOKA, CommonKADS, and the 47-step protocol provide approaches to run a project from beginning to completion, as well as maintaining best practice.

1.5 What are KBSs?

      A knowledge-based framework is a system that utilizes AI tools in problem-solving systems to assist human decision-making, understanding, and intervention.

      There are two core components of the KBSs:

       • Information base (consists of a collection of details and a set of laws, structures, or procedures).

       • Inference engine (Responsible for the extension of the information base to the issue at hand).

      In contrast to human expertise, there are pros and cons to utilizing KBSs.

      1.5.1 What is KBE?

      It starts with a discussion about what KBE is in this book and begins with a simple definition: Knowledge-based Engineering (KBE) uses the knowledge of product and operation, which was collected and retained in specific software applications, to enable its direct usage and reuse in the development of new products and variants. KBE’s implementation consists of applying a specific class of computing tools, called the KBE systems, which enable engineers to acquire and reuse engineering knowledge using methods and methodologies. The name of the KBE architecture is derived from the mixture of KBS and engineering, which are one of the major outcomes of AI. In the 1970s, KBE systems demonstrate the advancement of the KBS by applying the special engineering industry requirements. KBE systems combine KBS rule-based logic technologies with engineering data analysis and geometry like CAD.

For these reasons, a traditional KBE architecture provides the user with a programming language that is generally object-oriented and one (something more) embedded or closely connected CAD engine. The vocabulary СКАЧАТЬ