REUSE OF INFORMATION BASED ON THE INTERPRETATION OF KNOWLEDGE
DOI:
https://doi.org/10.30837/ITSSI.2023.24.062Keywords:
software engineering; knowledge bases; reuse of knowledge; algebra of finite predicates; facts; rulesAbstract
Recently, much attention has been paid to the creation of knowledge bases that contain millions of facts about various objects of the real world. One of the key aspects of knowledge management is the reuse of previously acquired knowledge. The subject of research is the processes of knowledge reuse and the creation of software systems based on knowledge bases. Knowledge interpretation is one approach to knowledge reuse, which consists in deriving new knowledge based on existing facts in the knowledge base. The purpose of the study is to increase the efficiency of knowledge reuse in software systems based on knowledge bases due to automatic rule extraction. To achieve the goal, the following tasks were solved: approaches to structuring the facts available in the database were considered, a qualitative analysis of the possibility of applying automatic methods of rule construction and derivation was carried out. The task of predicting the connection between a pair of entities, which determines the presence of a relationship for facts, is considered. A generalized approach to the presentation of facts is proposed, which allows the use of efficient rule-finding algorithms. The following methods are used to solve the given problem: the algebra of finite predicates and predicate operations for knowledge representation, methods for predicting the connection between a pair of entities based on representative learning for automatically obtaining rules. The following results were obtained: an approach to rule formation was considered, which allows structuring existing facts as a set of binary predicates and applying automatic methods of rule construction and derivation. It is concluded that the limitation of knowledge reuse is the structure of the knowledge base and the software used to support it. The article formulates the principles of building specific concentrator predicates for the representation of attributes, which allows generalizing the predicate representation of facts and applying automatic methods of rule extraction, which increases the efficiency of knowledge reuse. Conclusions: the application of the method and mechanism of identification based on predicate operations and specific predicates, which automatically extracts attributes from the knowledge base, together with the quality assessment of the derived rules, made it possible to propose a generalized approach for presenting facts and use effective rule search algorithms, which allows to increase the efficiency of reuse knowledge in software systems.
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