By Nelson M. Mattos
This ebook addresses the advance of a brand new new release of platforms, wisdom Base administration platforms (KBMS), specifically developed for powerful and effective administration of data bases, with the purpose of filling a part of the technological hole among synthetic intelligence and databases. The publication first investigates intimately the layout technique, the structure, and the operating tools of information established platforms (KS) with the intention to indicate the most important features of the sphere in addition to its present boundaries, which serve then as foundation for a precise formula of KS specifications. An research and overview of different techniques (e.g., traditional DBS, non-standard DBS, coupling professional platforms and DBS) to wisdom administration is given. The ebook exhibits that during constructing KBMS, the event received through the research of every of those ways is very very important when you consider that they supply the fundamental strategies for development KBMS. The ways shouldn't be considered as entire and ultimate yet as a part of examine paintings in the direction of KBMS. a unique structure is defined for KBMS which integrates the performance, flexibility and modeling energy of DBS and AI. the most a part of the publication offers with all very important architectural difficulties of KBMS: tools for wisdom illustration with particular emphasis on abstraction techniques, language proposals, and ideas for functionality development. The ebook relies on sensible event amassed over 5 years of winning learn in coupling present specialist platforms and DBS, extending DBS with deductive functions, and specifically within the layout and implementation of a KBMS prototype. hence the book's proposals are illustrated with particular descriptions in their awareness in current platforms or prototypes.
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Additional resources for An Approach to Knowledge Base Management
Generally, prototypes perform poorly at the start because of an inexact understanding of the expert's behaviors, an erroneous transformation of abstract concepts of the domain, an incorrect definition of heuristic rules, or a neglect of some important aspects. This does not reflect, however, incompetence of the knowledge engineer or the expert. On the contrary, approaches free of errors hardly exist. Note that experts are denoted in this way because they have large amounts of knowledge and not because they think about or verbalize it.
Thus, precise knowledge can be stated as assertions over objects that take the form of firstorder predicates with functions and equality [Ko79]. According to this view, a KB is a collection of logical formulas providing a description of the world. ) of the logical formulas. Logic has the advantage of offering a sound and complete set of inference rules. Uple uses of the same piece of knowledge, although it is represented just once in the KB. Furthermore, it usually possesses a well-understood and well-accepted formal semantics [Me64], and a very simple notation, which leads to a KB description that is easily understandable [My80].
In other words, this AI field has been working on the development of schemes that directly reflect the user's natural conceptualization of the universe of discourse. 33 By doing this, very powerful and sufficiently precise schemes to represent knowledge have been developed. Some of these schemes emphasize the declarative charactedstics of knowledge and are, for this reason, very appropriate in describing the passive parts of the domain knowledge because of its inactive nature. e,, active) knowledge of the application world and of the human experts.