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BUILDING AN EFFECTIVE KNOWLEDGE MANAGEMENT SYSTEM IN THE CONCEPT OF ARTIFICIAL INTELLIGENCE SYSTEM ORGANIZATION
Resumo
Objective: The study aims to analyze the design and operation of database and knowledge base machines within the concept of artificial intelligence system organization, focusing on creating AI systems to model solutions described by mathematical operations over natural language at logical and hardware levels.
Method: The research utilized a qualitative approach, reviewing scholarly articles from scientific journals to explore the organization of AI systems, particularly through the use of finite predicates and universal functional transformers.
Results: The study identifies that the key challenge in building a management system at the semantic or semantic-pragmatic level lies in constructing information databases (data and knowledge) related to the subject industry and developing output mechanisms for deriving necessary decisions. The mathematical structure of data in declarative languages is grounded in systems of predicate equations.
Conclusion: The paper concludes that building effective AI-based knowledge management systems involves integrating complex data and knowledge structures at semantic levels to enhance decision-making processes, highlighting the need for advanced computational architectures to handle the semantic complexity of data.
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DOI: http://dx.doi.org/10.21902/Revrima.v4i46.7576
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