By Nelson M. Mattos
This publication addresses the improvement of a brand new iteration of platforms, wisdom Base administration platforms (KBMS), in particular developed for potent and effective administration of information bases, with the purpose of filling a part of the technological hole among synthetic intelligence and databases. The ebook first investigates intimately the layout approach, the structure, and the operating equipment of information dependent structures (KS) in an effort to indicate the major features of the sector in addition to its present obstacles, which serve then as foundation for a precise formula of KS specifications. An research and review of alternative ways (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 adventure bought via the research of every of those ways is very very important due to the fact that they supply the fundamental suggestions for construction KBMS. The methods shouldn't be seen 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 strength of DBS and AI. the most a part of the e-book bargains with all vital architectural difficulties of KBMS: equipment for wisdom illustration with certain emphasis on abstraction options, language proposals, and ideas for functionality development. The e-book is predicated on sensible event collected over 5 years of winning study in coupling current professional structures and DBS, extending DBS with deductive services, and in particular within the layout and implementation of a KBMS prototype. hence the book's proposals are illustrated with unique descriptions in their awareness in current platforms or prototypes.
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Additional info for An Approach to Knowledge Base Management
As such, it starts with the goal specification and tries to find rules whose conclusions match this goal. After finding such rules, it formulates as new goals the problems of satisfying the rule conditions in order to apply them. , by exploiting some conflict resolution strategy. Since a rule frequently has many conclusions, the process of satisfying a goal is usually transformed into the problem of satisfying many subgoals. , when they match some assertion of the KB. 8 shows a backward reasoning process in which the goal is fulfilled after the application of some rules and the satisfaction of the subgoals sg14, sg15, sg16, sg17, and sg18.
1 Generate-and-Test Generate-and-test, also called reasoning by elimination, translates the idea of considering all possible solutions to a particular goal, and rules out those with low plausibility. The idea behind this strategy is to prune the search space as early as possible so that the system can reduce its search activities. To do this, the knowledge engineer must partition the search space in such a way that early pruning can be achieved. The difficulty often found in this approach is that some- 50 times there is no practical way to consider all possible solutions to the goal at hand.
Hence, XPS should • support the acquisition of knowledge, • assume its storage and management, • apply it to solve problems, and • explain their solving process. 2. Knowledge Base (KB) A KB usually contains, in a declarative form, three different things. , domain knowledge). ). 2: Overall XPS architecture specific to the application domain and to the particular class of problem that the XPS is set up to solve. , programs which are not called by other programs in the ordinary way but are instead activated by the control structures whenever certain conditions hold in the knowledge) as for example rules.
An Approach to Knowledge Base Management by Nelson M. Mattos