Data mining in relational systems

Філатов, В. О.; Семенець, В. В.; Золотухін, О. В.

Публікація:
Data mining in relational systems

dc.contributor.author	Філатов, В. О.
dc.contributor.author	Семенець, В. В.
dc.contributor.author	Золотухін, О. В.
dc.date.accessioned	2020-10-14T17:05:39Z
dc.date.available	2020-10-14T17:05:39Z
dc.date.issued	2020
dc.description.abstract	The subject of the research is methods of relational database mining. The purpose of the research is to develop scientificallygrounded models for supporting intelligent technologies for integrating and managing information resources of distributed computing systems. Explore the features of the operational specification of the relational data model. To develop a method for evaluating a relational data model and a procedure for constructing functional associative rules when solving problems of mining relational databases. In accordance with the set research goal, the presented article considers the following tasks: analysis of existing methods and technologies for data mining. Research of methods for representing intelligent models by means of relational systems. Development of technology for evaluating the relational data model for building functional association rules in the tasks of mining relational databases. Development of design tools and maintenance of applied data mining tasks; development of applied problems of data mining. Results: The analysis of existing methods and technologies for data mining is carried out. The features of the structural specification of a relational database, the formation of association rules for building a decision support system are investigated. Information technology has been developed, a methodology for the design of information and analytical systems, based on the relational data model, for solving practical problems of mining, practical recommendations have been developed for the use of a relational data model for building functional association rules in problems of mining relational databases, conclusion: the main source of knowledge for database operation can be a relational database. In this regard, the study of data properties is an urgent task in the construction of systems of association rules. On the one hand, associative rules are close to logical models, which makes it possible to organize efficient inference procedures on them, and on the other hand, they more clearly reflect knowledge than classical models. They do not have the strict limitations typical of logical calculus, which makes it possible to change the interpretation of product elements. The search for association rules is far from a trivial task, as it might seem at first glance. One of the problems is the algorithmic complexity of finding frequently occurring itemsets, since as the number of items grows, the number of potential itemsets grows exponentially.	uk_UA
dc.identifier.citation	Filatov, V., Semenets, V., Zolotukhin, O. (2020), "Data mining in relational systems", Innovative Technologies and ScientificSolutions for Industries, No. 3 (13), P. 76–87.	uk_UA
dc.identifier.other	DOI: https://doi.org/10.30837/ITSSI.2020.13.076
dc.identifier.uri	http://openarchive.nure.ua/handle/document/13450
dc.language.iso	en	uk_UA
dc.publisher	ХНУРЕ	uk_UA
dc.subject	relational data model	uk_UA
dc.subject	associative patterns of data	uk_UA
dc.subject	data mining	uk_UA
dc.subject	intelligent system	uk_UA
dc.subject	information system	uk_UA
dc.title	Data mining in relational systems	uk_UA
dc.type	Article	uk_UA
dspace.entity.type	Publication