The original use of the term knowledge base was to describe one of the two sub-systems of an expert system. A knowledge-based system consists of a knowledge-base representing facts about the world and ways of reasoning about those facts to deduce new facts or highlight inconsistencies.[1]
Properties
The term "knowledge-base" was coined to distinguish this form of knowledge store from the more common and widely used term database. During the 1970s, virtually all large management information systems stored their data in some type of hierarchical or relationaldatabase. At this point in the history of information technology, the distinction between a database and a knowledge-base was clear and unambiguous.
A database had the following properties:
Flat data: Data was usually represented in a tabular format with strings or numbers in each field.
Multiple users: A conventional database needed to support more than one user or system logged into the same data at the same time.
Transactions: An essential requirement for a database was to maintain integrity and consistency among data accessed by concurrent users. These are the so-called ACID properties: Atomicity, Consistency, Isolation, and Durability.
Large, long-lived data: A corporate database needed to support not just thousands but hundreds of thousands or more rows of data. Such a database usually needed to persist past the specific uses of any individual program; it needed to store data for years and decades rather than for the life 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 just tables with numbers and strings, but pointers to other objects that in turn have additional pointers. The ideal representation for a knowledge base is an object model (often called an ontology in artificial intelligence literature) with classes, subclasses and instances.
Early expert systems also had little need for multiple users or the complexity that comes with requiring transactional properties on data. The data for the early expert systems was used to arrive at a specific answer, such as a medical diagnosis, the design of a molecule, or a response to an emergency.[1] Once the solution to the problem was known, there was not a critical demand to store large amounts of data back to a permanent memory store. A more precise statement would be that given the technologies available, researchers compromised and did without these capabilities because they realized they were beyond what could be expected, and they could develop useful solutions to non-trivial problems without them. Even from the beginning, the more astute researchers realized the potential benefits of being able to store, analyze, and reuse knowledge. For example, see the discussion of Corporate Memory in the earliest work of the Knowledge-Based Software Assistant program by Cordell Green et al.[2]
The volume requirements were also different for a knowledge-base compared to a conventional database. The knowledge-base needed to know facts about the world. For example, to represent the statement that "All humans are mortal". A database typically could not represent this general knowledge but instead would need to store information about thousands of tables that represented information about specific humans. Representing that all humans are mortal and being able to reason about any given human that they are mortal is the work of a knowledge-base. Representing that George, Mary, Sam, Jenna, Mike,... and hundreds of thousands of other customers are all humans with specific ages, sex, address, etc. is the work for a database.[3][4]
As expert systems moved from being prototypes to systems deployed in corporate environments the requirements for their data storage rapidly started to overlap with the standard database requirements for multiple, distributed users with support for transactions. Initially, the demand could be seen in two different but competitive markets. From the AI and Object-Oriented communities, object-oriented databases such as Versant emerged. These were systems designed from the ground up to have support for object-oriented capabilities but also to support standard database services as well. On the other hand, the large database vendors such as Oracle added capabilities to their products that provided support for knowledge-base requirements such as class-subclass relations and rules.
Internet as a knowledge base
The next evolution for the term knowledge-base was the Internet. With the rise of the Internet, documents, hypertext, and multimedia support were now critical for any corporate database. It was no longer enough to support large tables of data or relatively small objects that lived primarily in computer memory. Support for corporate web sites required persistence and transactions for documents. This created a whole new discipline known as Web Content Management.
The other driver for document support was the rise of knowledge management vendors such as Lotus Notes. Knowledge Management actually predated the Internet but with the Internet there was great synergy between the two areas. Knowledge management products adopted the term "knowledge-base" to describe their repositories but the meaning had a big difference. In the case of previous knowledge-based systems, the knowledge was primarily for the use of an automated system, to reason about and draw conclusions about the world. With knowledge management products, the knowledge was primarily meant for humans, for example to serve as a repository of manuals, procedures, policies, best practices, reusable designs and code, etc. In both cases the distinctions between the uses and kinds of systems were ill-defined. As the technology scaled up it was rare to find a system that could really be cleanly classified as knowledge-based in the sense of an expert system that performed automated reasoning and knowledge-based in the sense of knowledge management that provided knowledge in the form of documents and media that could be leveraged by humans.[5]
^ abHayes-Roth, Frederick; Donald Waterman; Douglas Lenat (1983). Building Expert Systems. Addison-Wesley. ISBN0-201-10686-8.
^Green, Cordell; D. Luckham; R. Balzer; T. Cheatham; C. Rich (1986). "Report on a knowledge-based software assistant". Readings in Artificial Intelligence and Software Engineering. Morgan Kaufmann: 377–428. doi:10.1016/B978-0-934613-12-5.50034-3. Retrieved 1 December 2013.
^Feigenbaum, Edward (1983). The Fifth Generation: Artificial Intelligence and Japan's Computer Challenge to the World. Reading, MA: Addison-Wesley. p. 77. ISBN0-201-11519-0. Your database is that patient's record, including history... vital signs, drugs given,... The knowledge base... is what you learned in medical school... it consists of facts, predicates, and beliefs...
^Jarke, Mathias (1978). "KBMS Requirements for Knowledge-Based Systems" (PDF). Logic, Databases, and Artificial Intelligence. Berlin: Springer.
^Krishna, S (1992). Introduction to Database and Knowledge-base Systems. Singapore: World Scientific Publishing. ISBN981-02-0619-4.
knowledge, base, this, article, needs, additional, citations, verification, please, help, improve, this, article, adding, citations, reliable, sources, unsourced, material, challenged, removed, find, sources, news, newspapers, books, scholar, jstor, june, 2014. This article needs additional citations for verification Please help improve this article by adding citations to reliable sources Unsourced material may be challenged and removed Find sources Knowledge base news newspapers books scholar JSTOR June 2014 Learn how and when to remove this template message A knowledge base KB is a technology used to store complex structured and unstructured information used by a computer system The initial use of the term was in connection with expert systems which were the first knowledge based systems Contents 1 Original usage of the term 2 Properties 3 Internet as a knowledge base 4 See also 5 References 6 External linksOriginal usage of the term EditThe original use of the term knowledge base was to describe one of the two sub systems of an expert system A knowledge based system consists of a knowledge base representing facts about the world and ways of reasoning about those facts to deduce new facts or highlight inconsistencies 1 Properties EditThe term knowledge base was coined to distinguish this form of knowledge store from the more common and widely used term database During the 1970s virtually all large management information 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 knowledge base was clear and unambiguous A database had the following properties Flat data Data was usually represented in a tabular format with strings or numbers in each field Multiple users A conventional database needed to support more than one user or system logged into the same data at the same time Transactions An essential requirement for a database was to maintain integrity and consistency among data accessed by concurrent users These are the so called ACID properties Atomicity Consistency Isolation and Durability Large long lived data A corporate database needed to support not just thousands but hundreds of thousands or more rows of data Such a database usually needed to persist past the specific uses of any individual program it needed to store data for years and decades rather than for the life 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 just tables with numbers and strings but pointers to other objects that in turn have additional pointers The ideal representation for a knowledge base is an object model often called an ontology in artificial intelligence literature with classes subclasses and instances Early expert systems also had little need for multiple users or the complexity that comes with requiring transactional properties on data The data for the early expert systems was used to arrive at a specific answer such as a medical diagnosis the design of a molecule or a response to an emergency 1 Once the solution to the problem was known there was not a critical demand to store large amounts of data back to a permanent memory store A more precise statement would be that given the technologies available researchers compromised and did without these capabilities because they realized they were beyond what could be expected and they could develop useful solutions to non trivial problems without them Even from the beginning the more astute researchers realized the potential benefits of being able to store analyze and reuse knowledge For example see the discussion of Corporate Memory in the earliest work of the Knowledge Based Software Assistant program by Cordell Green et al 2 The volume requirements were also different for a knowledge base compared to a conventional database The knowledge base needed to know facts about the world For example to represent the statement that All humans are mortal A database typically could not represent this general knowledge but instead would need to store information about thousands of tables that represented information about specific humans Representing that all humans are mortal and being able to reason about any given human that they are mortal is the work of a knowledge base Representing that George Mary Sam Jenna Mike and hundreds of thousands of other customers are all humans with specific ages sex address etc is the work for a database 3 4 As expert systems moved from being prototypes to systems deployed in corporate environments the requirements for their data storage rapidly started to overlap with the standard database requirements for multiple distributed users with support for transactions Initially the demand could be seen in two different but competitive markets From the AI and Object Oriented communities object oriented databases such as Versant emerged These were systems designed from the ground up to have support for object oriented capabilities but also to support standard database services as well On the other hand the large database vendors such as Oracle added capabilities to their products that provided support for knowledge base requirements such as class subclass relations and rules Internet as a knowledge base EditThe next evolution for the term knowledge base was the Internet With the rise of the Internet documents hypertext and multimedia support were now critical for any corporate database It was no longer enough to support large tables of data or relatively small objects that lived primarily in computer memory Support for corporate web sites required persistence and transactions for documents This created a whole new discipline known as Web Content Management The other driver for document support was the rise of knowledge management vendors such as Lotus Notes Knowledge Management actually predated the Internet but with the Internet there was great synergy between the two areas Knowledge management products adopted the term knowledge base to describe their repositories but the meaning had a big difference In the case of previous knowledge based systems the knowledge was primarily for the use of an automated system to reason about and draw conclusions about the world With knowledge management products the knowledge was primarily meant for humans for example to serve as a repository of manuals procedures policies best practices reusable designs and code etc In both cases the distinctions between the uses and kinds of systems were ill defined As the technology scaled up it was rare to find a system that could really be cleanly classified as knowledge based in the sense of an expert system that performed automated reasoning and knowledge based in the sense of knowledge management that provided knowledge in the form of documents and media that could be leveraged by humans 5 See also EditContent management Database Enterprise bookmarking Information repository Knowledge based system Knowledge graph Knowledge management Microsoft Knowledge Base Diffbot Ontology engineering Semantic network Symbolic artificial intelligence Text mining Vadalog Wikidata YAGOReferences Edit a b Hayes Roth Frederick Donald Waterman Douglas Lenat 1983 Building Expert Systems Addison Wesley ISBN 0 201 10686 8 Green Cordell D Luckham R Balzer T Cheatham C Rich 1986 Report on a knowledge based software assistant Readings in Artificial Intelligence and Software Engineering Morgan Kaufmann 377 428 doi 10 1016 B978 0 934613 12 5 50034 3 Retrieved 1 December 2013 Feigenbaum Edward 1983 The Fifth Generation Artificial Intelligence and Japan s Computer Challenge to the World Reading MA Addison Wesley p 77 ISBN 0 201 11519 0 Your database is that patient s record including history vital signs drugs given The knowledge base is what you learned in medical school it consists of facts predicates and beliefs Jarke Mathias 1978 KBMS Requirements for Knowledge Based Systems PDF Logic Databases and Artificial Intelligence Berlin Springer Krishna S 1992 Introduction to Database and Knowledge base Systems Singapore World Scientific Publishing ISBN 981 02 0619 4 External links Edit Scholia has a topic profile for Knowledge base The template below Computable knowledge is being considered for deletion See templates for discussion to help reach a consensus This logic related article is a stub You can help Wikipedia by expanding it vte Retrieved from https en wikipedia org w index php title Knowledge base amp oldid 1129860537, wikipedia, wiki, book, books, library,
