Topic 185

Collection/creation of a knowledge base by Tanay Khandelwal

A knowledge base (or knowledgebase; abbreviated KB, kb or Δ) is a special kind of database for knowledge management. It provides the means for the computerized collection, organization, and retrieval of knowledge.

Types

Knowledge bases are categorized into two major types:

• Machine-readable knowledge bases store knowledge in a computer-readable form, usually for the purpose of having automated deductive reasoning applied to them. They contain a set of data, often in the form of rules that describe the knowledge in a logically consistent manner. Logical operators such as And (conjunction), Or (disjunction), material implication and negation may be used to build it up from the atomic knowledge. Consequently classical deduction can be used to reason about the knowledge in the knowledge base.

• Human-readable knowledge bases are designed to allow people to retrieve and use the knowledge they contain, primarily for training purposes. They are commonly used to capture explicit knowledge of an organization, including troubleshooting, articles, white papers, user manuals and others. The primary benefit of such a knowledge base is to provide a means to discover solutions to problems that have known solutions which can be re-applied by others, less experienced in the problem area.

The most important aspect of a knowledge base is the quality of information it contains. The best knowledge bases have carefully written articles that are kept up to date, an excellent information retrieval system (search engine), and a carefully designed content format and classification structure.

A knowledge base may use an ontology to specify its structure (entity types and relationships) and its classification scheme. An ontology, together with a set of instances of its classes constitutes a knowledge base.
Determining what type of information is captured, and where that information resides in a knowledge base is something that is determined by the processes that support the system. A robust process structure is the backbone of any successful knowledge base.

Some knowledge bases have an artificial intelligence component. These kinds of knowledge bases can suggest solutions to problems sometimes based on feedback provided by the user, and are capable of learning from experience.

As a result of global competition and rapid technological progress, engineers seek quick and innovative solutions for technical problems using fewer resources. This is necessary in order to improve products and processes so that a corporation can maintain its leadership in and share of the market. It is possible to use one of two approaches to solve a technical problem:

1. Independent problem research, personal search for innovative solutions.

2. Reference to similar technical problems that have previously been solved by other engineers in the same or other domains. Knowledge transfer to the problem in question.

Both approaches have their own drawbacks and benefits. Let’s consider some of them. While conducting personal research about the problem in question, there is a risk of wasting time and resources on a problem that has already been solved.

On the other hand, when you attempt to refer to a similar problem solution reached by other engineers, the results might not always be convincing. Practice shows that knowledge incorporated in patents is in some cases insufficient to solve a particular problem. The reasons for this might be summarized as follows:

1. The majority of similar problems are found in other domains. This makes the search for solutions more complex, because the engineer is not aware of the domains to explore for the problem in question.

2. The number of patents is rapidly increasing. The procedure of searching and studying the pertinent patents requires more time and effort.

3. Patents are legal documents. As a rule, they contain some information that is irrelevant for the engineer to solve a problem. The engineer has to analytically extract problem-related information and examine the essence of the problem described in the patent.

A more unique and systematic approach to handle the problem in question is to use Multimedia Knowledge Bases.

Sources:
http://en.wikipedia.org/wiki/Knowledge_Base
http://consulting.effectivesoft.com/why_kb.html


or

Collection/creation of a knowledge base by Ronald

First of all, what is a knowledge base (or knowledgebase)? A knowledge base (and it is abbreviated by writing KB, kb or Δ) is a special kind of database for knowledge management. It provides the means for the computerized collection, organization, and retrieval of knowledge. Just as it has become standard practice to write database as one word it is increasingly common in computer science to write knowledgebase as one word.

There are two major types of knowledge bases. First, there is the machine-readable knowledge base. This type stores knowledge in a computer-readable form, usually for the purpose of having automated deductive reasoning applied to them. It contains a set of data, often in the form of rules that describe the knowledge in a logically consistent manner. Logical operators such as “And” (which is a conjunction), “Or” (which is a disjunction), material implication and negation may be used to build it up from the atomic knowledge. Consequently classical deduction can be used to reason about the knowledge in the knowledge base.

The second type is known as the human-readable knowledge base. This type is designed to allow people to retrieve and use the knowledge they contain, primarily for training purposes. IT is commonly used to capture explicit knowledge of an organization, including troubleshooting, articles, white papers, user manuals and others things. The main benefit of this kind of knowledge base is to provide a means to discover solutions to problems that have known solutions which then can be re-applied by others, which are possibly less experienced in the problem area.

The most important part of a knowledge base is not the quantity of the information it contains; but the quality. The truly best knowledge bases have carefully written articles that are kept up to date, and contain an excellent information retrieval system (search engine), and a carefully designed content format and classification structure.
A knowledge base may use an ontology to specify its structure (entity types and relationships) and its classification scheme. An ontology is a data model that represents a set of concepts within a domain and the relationships between those concepts. It is used to reason about the objects within that domain.

Some knowledge bases have an artificial intelligence component. These kinds of knowledge bases can suggest solutions to problems sometimes based on feedback provided by the user, and are capable of learning from experience. Knowledge representation, automated reasoning and argumentation are the three main active areas of research of artificial intelligence