Knowledge base – Wikipedia

A Basic knowledge (also identified with the English term knowledge base and with the acronym KB ) is a special type of database for the management of knowledge for corporate, cultural or educational purposes. It therefore constitutes an environment aimed at facilitating the collection, organization and distribution of knowledge.

A basis of knowledge of corporate interest normally proposes the explicit knowledge of an organization, including that which can serve to resolve problems, and concern articles, relationships, manuals for users and more. A knowledge base should respect a well -designed classification structure, observe (few) certain formats for the contents and have a search engine.

The most important aspect of a knowledge base is the type of information it contains. A base of knowledge that becomes a site from where to download irrelevant information sees its compromised role, just like irrelevant information. Make sure that the most relevant and updated information is present in a knowledge base is essential for its success, in order not to mention the fact of having an excellent information recovery system (search engine).

Determine the type of information and where these reside in the basis of knowledge is an activity that is determined according to the processes that support the system. A robust process of creating the structure is the backbone of a successful knowledge base.

The original use of the term knowledge base was to describe one of the two subsystems of an expert system. A knowledge -based system consists of a basis of knowledge that represents facts on the world and an 8 reasoning on those facts and uses rules and other forms of logic to deduce new facts or highlight inconsistencies ^[first] .

The term “Knowledge-Base” was coined to distinguish this form of the Knowledge Store from database of more common and widely used terms. During the 1970s, practically all large management systems stored their data in some type of hierarchical or relational database. At this point in the history of information technology, the distinction between a database and a base of knowledge was clear and unequivocal.

A database had the following properties:

• “Flat” data: the data were generally represented in a tabular format with strings or numbers in every field.
• Multi-UTUMENTS: a conventional database necessary to support more than one user or system connected to the same data at the same time.
• Transactions: an essential requirement for a database was to maintain the integrity and consistency between the data to which simultaneous users accessed. These are the so -called Acid properties: atomicity, consistency, isolation and durability.
• Large and long -lasting data: a corporate database had to support not only thousands but hundreds of thousands or more lines of data. A database of this type normally necessary to persist beyond the specific uses of each individual program; He needed to store data for years and decades rather than for the duration of a program.

The first knowledge -based systems had data needs that were the opposite of these database requirements. An expert system requires structured data. Not only tables with numbers and strings, but pointers to other objects who in turn have additional aims. The ideal representation for a knowledge base is a model to objects (often called ontology in literature on artificial intelligence) with classes, subclasses and instances.

The first expert systems also had little need for more users or the complexity deriving from the request for transactional ownership on data. The data for the first experienced systems were used to get to a specific response, such as a medical diagnosis, the project of a molecule or a response to an emergency ^[first] . Once the solution is known to the problem, there was no critical request to store large quantities of data in a permanent memory archive. A more precise statement would be that, given the technologies available, the researchers compromised and made unless these skills because they realized that they were beyond what could be expected and could develop useful solutions to non -trivial problems without them. From the beginning, the most cunning researchers have realized the potential advantages of being able to archive, analyze and reuse knowledge. For example, see the discussion on the company memory in the first work of the Knowledge-Based Software Assistant program of Cordell Green ^[2] .

The volume requirements were also different for a basic know -how compared to a conventional database. The basis of knowledge necessary to know the facts on the world. For example, to represent the statement that “all human beings are fatal”. A database in general could not represent this general knowledge, but instead it would need to store information on thousands of tables that represented information on specific human beings. Represent that all humans are fatal and being able to reason on a human data that are mortal is the work of a base of knowledge. Represent that George, Mary, Mike, … and hundreds of thousands of other customers are all human beings with certain age, sex, address, etc., is the work for a database ^{[3] [4]} .

When expert systems have gone from being prototypes to systems distributed in corporate environments, the requirements for data storage have quickly started overlapping the requirements of the standard database for multiple users distributed with transactions support. Initially, the question could be seen in two different but competitive markets. Databases oriented to objects such as Versant emerged from the communities AI and Object-Oriented. These were systems designed from scratch to support object -oriented features, but also to support standard database services. On the other hand, the large database suppliers like Oracle added functionality to their products that have provided support for the requirements of the knowledge base such as the relationships and rules of class-Sottoclasse.

The subsequent evolution of the term Knowledge Base was the Internet. With the advent of the internet, documents, hypertexts and multimedia support were now fundamental for any corporate database. It was no longer enough to support large data tables or relatively small objects that resided mainly in the memory of the computer. Support for company websites required persistence and transactions for documents. This has created a completely new discipline known as web content management.

The other driver for the support of documents was the rise of knowledge management suppliers such as Lotus Notes. The management of knowledge actually preceded the Internet, but with the Internet there was a great synergy between the two areas. The knowledge management products adopted the term “knowledge base” to describe their archives, but the meaning had a thin difference. In the case of previous systems based on knowledge, knowledge was mainly for the use of an automated system, to reason and draw conclusions about the world. With knowledge management products, it was mainly intended for human beings, for example to act as an archive of manuals, procedures, policies, best practices, projects and reusable codes, etc. In both cases the distinctions between uses and types of systems were poorly defined ^[5] .