Development of Object's Structured Information Field with Specific Properties for its Semantic Model Building

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Abstract
Implementation of applied artificial intelligence systems requires novel approaches to the formalization and modeling of domain knowledge. Collecting data about information objects, which represent components of intelligent systems, calls for creation of reliable information field of the object with predetermined restrictions. These restrictions affect the structure of the field and ensure its filling from the open Web environment. The paper proposes means and methods of pre-processing the data field (classification, clustering, associative relationships) and integration of accumulated resources. Also, we suggest a method of step-by-step development of the structure of the information field, which begins with the definition of the information object of research around which the field will be built. The problem of the reliability of information resources from which the information field is filled is solved by analytical methods and the method of semantic analysis of metadata. It's provided interpretation, recognition, and selection of reliable data relevant to the issue being solved. The issue of accuracy of data recognition and interpretation of accumulated data is solved on the basis of methods for calculating semantic proximity and semantic distance between semantic models. The practical implementation of the obtained results created a multi-agent e-commerce system based on the ontological approach.

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