W ramach prac badawczych realizowanych w obszarze zastosowań metod AI, VR i IoE w diagnostyce, nadzorowaniu i sterowaniu procesów w Przemyśle 4.0 opublikowany został artykuł w Advances in Intelligent Systems and Computing.
Dymora P., Mazurek M: Performance Assessment of Selected Techniques and Methods Detecting Duplicates in Data Warehouses. Theory and Applications of Dependable Computer Systems. DepCoS-RELCOMEX 2020. Advances in Intelligent Systems and Computing, vol 1173. Springer, Cham
Abstract
A significant and current research problem, as well as a practical one, is the problem of deduplication in databases. The solution of this problem is applicable, e.g., in the context of the following situations in which are stored apparently different records, which actually refer to the same entity (objects, individuals, etc.) in the real world. In such cases, the purpose is to identify and reconcile such records or to eliminate duplication. The paper describes algorithms for finding duplicates and implements them in the developed data warehouse. Efficiency and effectiveness tests were also carried out for sample data contained in individual tables of the warehouse. The work aims to analyze the existing methodologies for detecting similarities and duplicates in data warehouses, to implement algorithms physically, and to test their effectiveness and efficiency. A large scale of data created by IoT devices leads to the consumption of communication bandwidth and disk space because the data is highly redundant. Therefore, correct deduplication of information is necessary to eliminate redundant data.
Prace badawcze w tym zakresie realizowane były w ramach zadania 2 projektu „Regionalne Centrum Doskonałości Automatyki i Robotyki, Informatyki, Elektrotechniki, Elektroniki oraz Telekomunikacji Politechniki Rzeszowskiej" współfinansowanego ze środków Ministerstwa Nauki i Szkolnictwa Wyższego.
