Emulating Human Learning with Knowledge Acquisition
As automated reasoning technology makes its way into the software mainstream, it is receiving more attention and scrutiny than ever before. Executives worldwide are only beginning to get a sense of how this type of technology can benefit their organization. Toward this pursuit of fortifying software applications with human-like learning capabilities comes a new set of buzzwords and associated confusion surrounding the significance and distinction between the various terms. Artificial intelligence and machine learning come to mind, for example.
Here, we consider one such technology—knowledge acquisition (KA).
There are several key points of contrast between KA and the more mainstream learning technologies. One distinguishing factor is that the manner in which knowledge is stored in many KA applications depends on the intended use of the knowledge. For example, latent knowledge acquired from a departing staff member for the purposes of documentation will be stored differently than knowledge of business requirements gathered from company stakeholders.
Another area of contrast is that KA learning agents concern themselves with not only the data to be learned, but other meta factors such as the reputation of input sources and the probabilities of inferences between the various pieces of information. KA algorithms must also deal with contradictions between different pieces of acquired knowledge. More traditional learning technologies either don’t consider these factors at all, or consider them in more limited form.
KA technology is used in several settings and for many purposes. According to one approach, information is stored in a domain-independent format such that connections to previously learned knowledge may be established later—often in ways that could not have been conceived when the information was first learned. Other KA uses involve storing knowledge as text for the purposes of searching, and also organizing knowledge using word or phrase concept relationships or ontologies.
KA has been studied and used extensively for years by the United States military, academic researchers, and various organizations having needs for such intelligence capabilities. However, KA is not out of reach of everyday modern business. It is one of many areas in which Prolifogy offers world-class Ph.D. level applied research expertise.
To learn more about how knowledge acquisition and other cutting-edge technologies can be applied to your existing or upcoming project, call Prolifogy at (855)-PROLIFOGY or contact us through our web site.