KNOWLEDGE MANAGEMENT

Applied Logic Laboratory has developed a complex toolset for knowledge management. The individual tools support knowledge acquisition, representation and reasoning.

The knowledge acquisition toolset offers methods for extracting formalised knowledge from recorded data and information. Some of these methods include intelligent data analysis tools. Textual information can be processed by semantic methods which help to convert free text into formal descriptions. Special software modules have been developed for formalising knowledge stored in textual or graphical clinical guidelines. A rich set of data mining techniques including plausible reasoning, statistical methods, connectionist and self-organising techniques has also been implemented.

The company has elaborated various methods of knowledge representation. Special language has been developed for representing guidelines as knowledge. For medical applications, customers can use a symptom-syndrome language to represent diagnostic criteria.

Applied Logic Laboratory has been particularly active in developing reasoning and inference methods using the knowledge stored. These techniques include vvarious innovative methods for plausible reasoning including statistical, logical and fuzzy logic methods, case-based reasoning and methods based on analogy. These methods serve for abductive, deductive and inductive inference. The company has worked out a special threshold logic technique for diagnostic reasoning.

Knowledge representation

ALL developed various methods of knowledge representation. One of them is a special method that permits to represent guidelines as knowledge. Moreover a special symptom-syndrome language and the corresponding threshold logic for diagnostic reasoning were developed as an efficient tool for knowledge representation.

Knowledge acquisition

ALL worked out more methods to acquire information and knowledge from measuring data conglomerate belonging to a concrete field of problem. One of these methods is built to a special logic basis, worked out for this aim. This is the so called cognitive logic that defines process appropriate for acquiring new information from the observation data. This process is set up by the synthesis of various logical operators. These are deductive, inductive, analogy based and abductive operators. The model based reasoning methodology might be connected here.

ALL copes with acquiring coherency based on the traditional data analysing statistic method of information acquisition and the neuron- net based method of information acquisition.

Knowledge based systems

ALL is committed about the research and development activity related to knowledge based systems, as the intelligent- and cognitive systems. ALL worked out lot of application systems that give task solving and decision making support. That’s why ALL worked out expert systems, decision support forecasting systems and diagnostic decision support systems too. ALL elaborated a geological and geophysical modelling and forecasting system among others (for example for locating the possible quarries of mineral oil and other minerals). Lot of medical expert systems were produced based on the principles of the knowledge based intelligent partner system, as for example the consultancy partner systems for the fields of immunology, nephrology, cardiology, internal medicine, diaetology etc. Our most recent development supports the ambulance services.

Knowledge transfer

ALL dealt with the epistemological examination of the knowledge, and worked out the method of handling codified and precedent knowledge. Related to that, we examined the qualities of these types of knowledge. We defined the model of the originating and developing of knowledge. We worked out a knowledge handling methodology based on this model. We elaborated the structural and functional model of knowledge transfer based on the results of that. The structural model defines few of the efficient solutions of structuring the educational system. We examined the possible ways of implementing knowledge transfer optimally in the educational systems. We analyzed the bounds and the possible prospects of the computer supported educational systems, the possible education- technical effects of the internet and the possible solutions.