![knowledge base one word or two knowledge base one word or two](https://sites.miis.edu/kb/files/2010/08/schedule.png)
![knowledge base one word or two knowledge base one word or two](https://d33v4339jhl8k0.cloudfront.net/docs/assets/56c6e208c697915005a72a5f/images/57cd3787903360649f6e5326/file-4wvr1XHla0.png)
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. These were systems designed from the ground up to have support for object-oriented capabilities but also to support standard database services as well. From the AI and Object-Oriented communities, object-oriented databases such as Versant emerged. Initially, the demand could be seen in two different but competitive markets. Īs 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. and hundreds of thousands of other customers are all humans with specific ages, sex, address, etc. Representing that George, Mary, Sam, Jenna, Mike. 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. 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. For example, to represent the statement that "All humans are mortal". The knowledge-base needed to know facts about the world. The volume requirements were also different for a knowledge-base compared to a conventional database.
#KNOWLEDGE BASE ONE WORD OR TWO SOFTWARE#
For example, see the discussion of Corporate Memory in the earliest work of the Knowledge-Based Software Assistant program by Cordell Green et al. Even from the beginning, the more astute researchers realized the potential benefits of being able to store, analyze, and reuse knowledge. 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. 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. 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. The ideal representation for a knowledge base is an object model (often called an ontology in artificial intelligence literature) with classes, subclasses and instances.Įarly expert systems also had little need for multiple users or the complexity that comes with requiring transactional properties on data. Not just tables with numbers and strings, but pointers to other objects that in turn have additional pointers. An expert system requires structured data. The first knowledge-based systems had data needs that were the opposite of these database requirements. 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. Large, long-lived data: A corporate database needed to support not just thousands but hundreds of thousands or more rows of data.These are the so-called ACID properties: Atomicity, Consistency, Isolation, and Durability. Transactions: An essential requirement for a database was to maintain integrity and consistency among data accessed by concurrent users.Multiple users: A conventional database needed to support more than one user or system logged into the same data at the same time.Flat data: Data was usually represented in a tabular format with strings or numbers in each field.At this point in the history of information technology, the distinction between a database and a knowledge-base was clear and unambiguous. During the 1970s, virtually all large management information systems stored their data in some type of hierarchical or relational database. The term "knowledge-base" was coined to distinguish this form of knowledge store from the more common and widely used term database. 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. The original use of the term knowledge base was to describe one of the two sub-systems of an expert system.