Knowledge Engineering for Modern Information Systems: A Comprehensive Guide to Capturing, Representing, and Utilizing Knowledge

Knowledge engineering is the process of capturing, representing, and utilizing knowledge in order to solve problems and make decisions. It is a vital part of modern information systems, as it allows computers to access and use knowledge in a way that is similar to how humans do.

Knowledge engineering has a long history, dating back to the early days of artificial intelligence (AI). In the 1950s and 1960s, AI researchers developed a number of knowledge-based systems, such as MYCIN and DENDRAL, which were able to solve complex problems in the domains of medicine and chemistry, respectively.

In the 1970s and 1980s, knowledge engineering became a more formalized discipline, with the development of a number of knowledge representation languages, such as KL-ONE and LOOM. These languages allowed knowledge engineers to represent knowledge in a structured and unambiguous way.

Knowledge Engineering for Modern Information Systems: Methods, Models and Tools (Smart Computing Applications Book 3)

by Sandeep Kautish

4.9 out of 5

Language	:	English
File size	:	5278 KB
Screen Reader	:	Supported
Print length	:	81 pages
Paperback	:	56 pages
Item Weight	:	7 ounces
Dimensions	:	8.5 x 0.13 x 11 inches
X-Ray for textbooks	:	Enabled

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In the 1990s and 2000s, knowledge engineering became increasingly integrated with other areas of AI, such as machine learning and natural language processing. This integration led to the development of new knowledge-based systems that were able to perform more complex tasks, such as diagnosing diseases, predicting customer behavior, and providing financial advice.

Today, knowledge engineering is an essential part of modern information systems. It is used in a wide variety of applications, such as:

• Expert systems: Expert systems are computer programs that emulate the knowledge and expertise of human experts. They are used in a variety of applications, such as medical diagnosis, financial planning, and legal advice.
• Decision support systems: Decision support systems are computer programs that help users make decisions by providing them with information and advice. They are used in a variety of applications, such as business planning, marketing, and healthcare.
• Knowledge management systems: Knowledge management systems are computer programs that help organizations capture, store, and share knowledge. They are used in a variety of applications, such as training, onboarding, and research.

The knowledge engineering process typically involves the following steps:

1. Knowledge acquisition: Knowledge acquisition is the process of gathering knowledge from a variety of sources, such as experts, documents, and databases.
2. Knowledge representation: Knowledge representation is the process of representing knowledge in a structured and unambiguous way.
3. Knowledge validation: Knowledge validation is the process of verifying the accuracy and completeness of knowledge.
4. Knowledge utilization: Knowledge utilization is the process of using knowledge to solve problems and make decisions.

The knowledge engineering process is iterative, and it may be necessary to repeat some of the steps multiple times in order to achieve the desired results.

Knowledge engineering is a challenging task, but it also offers a number of opportunities. Some of the challenges of knowledge engineering include:

• The knowledge acquisition bottleneck: Knowledge acquisition is often the most time-consuming and expensive part of the knowledge engineering process.
• The knowledge representation challenge: Knowledge representation is a complex task, and there is no one-size-fits-all solution.
• The knowledge validation challenge: Knowledge validation is essential to ensure the accuracy and completeness of knowledge.

However, knowledge engineering also offers a number of opportunities. Some of the opportunities of knowledge engineering include:

• The ability to solve complex problems: Knowledge engineering can be used to solve complex problems that cannot be solved by traditional methods.
• The ability to make better decisions: Knowledge engineering can be used to make better decisions by providing users with information and advice.
• The ability to capture and share knowledge: Knowledge engineering can be used to capture and share knowledge, which can lead to improved collaboration and innovation.

Knowledge engineering is a vital part of modern information systems. It allows computers to access and use knowledge in a way that is similar to how humans do. Knowledge engineering is a challenging task, but it also offers a number of opportunities. By overcoming the challenges and seizing the opportunities, knowledge engineering can help us to solve complex problems, make better decisions, and capture and share knowledge.

Knowledge Engineering for Modern Information Systems: Methods, Models and Tools (Smart Computing Applications Book 3)

by Sandeep Kautish

4.9 out of 5

Language	:	English
File size	:	5278 KB
Screen Reader	:	Supported
Print length	:	81 pages
Paperback	:	56 pages
Item Weight	:	7 ounces
Dimensions	:	8.5 x 0.13 x 11 inches
X-Ray for textbooks	:	Enabled

FREE