GIJANE – An Intelligent Entity for Knowledge Management
The purpose of databases is to turn data into knowledge for decision making. Although databases are appropriate solutions for businesses and enterprises, they often do not contain quality data. Fortunately, information comes in many forms and can be gathered in many ways. Because of this, when databases prove to be inadequate, other options for building useful models are available using generative grammar and semantic networks of information.
GIJANE is an intelligent entity (IE) based architecture that uses a rule-based classifications to emulate the cognition of a human being to define data sets, enterprise information models and expert systems.
Expert systems are models designed to emulate the behavior of a human being who is an expert at solving problems within a specialized subject. IEs are entities capable of achieving goals by defining the actions of other entities. Data mining, expert systems, and intelligent entities, guides and agents all exist under the umbrella of artificial intelligence problem-solving techniques. Although these approaches are discrete, each has a primary goal of creating an intelligent system.
GIJANE is an approach that uses elements of artificial intelligence to guide users; using generative grammar that links concepts together to form chains of concepts, cognition can be created. Think of the analogy of a network of neurons – when sending signals through this type of network they must be connected for the system to function at an optimal level. Chains of concepts that form artificial intelligence are built upon the ideas that exist in the neuropathways of all living organism (the simplest type of neural pathway is a monosynaptic [ie single connection] reflex pathway, like the jerk of the knee when stimulated) and, although neural networks seem complex at first they are definable, malleable and can be manipulated to achieve a variety of goals.
Because of its extensive scope, a single all-encompassing definition of artificial intelligence is difficult to define. One common theme is how to make computers do things that, for now, humans do better. An exponentially hard problem is a problem that cannot be solved with an algorithmic approach in a reasonable amount of time. The traveling salesman is a classic problem that fits this definition. A popular approach to this type of problem is the nearest neighbor heuristic. In databases, unlike physical geography the nearest neighbor is not always well-defined therefore with the introduction of business rules, the closest “neighbor” can be easily determined. Add a well defined syntax using generative grammar, depth-first, breath-first, forward chaining and backwards chaining capabilities to any extendable database and you have GIJANE – An Intelligent Entity!
GIJANE can determine the relatively high level description of a system that explains all of the pieces, how they communicate and interact with each other and in theory how they can evolve to meet new requirements and regulatory environments. It can be used to design concepts (without all attributes and keys) for any classified system (ie health, education and law) that is used in a business or enterprise setting, including governments and non-government organizations and is for use in designing those systems independently from how they are implemented. Every entity has been related to every other entity for optimal design and control.