ASA-graphs for efficient data representation and processing

• Autorzy: Horzyk Adrian , Bulanda Daniel , Starzyk Janusz A.

Identyfikatory

DOI

10.34768/amcs-2020-0053

• Języki publikacji: EN

Abstrakty

EN

Fast discovering of various relationships in data is an important feature of modern data mining, cognitive, knowledge-based, and explainable AI systems, including deep neural networks. The ability to represent a rich set of relationships between stored data and objects is essential for fast inferences, finding associations, representing knowledge, and extracting useful patterns or other pieces of information. This paper introduces self-balancing, aggregating, and sorting ASA-graphs for efficient data representation in various data structures, databases, and data mining systems. These graphs are smaller and use more efficient algorithms for searching, inserting, and removing data than the most commonly used self-balancing trees. ASA-graphs also automatically aggregate and count all duplicates of values and represent them by the same nodes, connecting them in order, and simultaneously providing very fast data access based on a binary search tree approach. The proposed ASA-graph structure combines the advantages of sorted lists, binary search trees, B-trees, and B+trees, eliminating their weaknesses. Our experiments proved that the ASA-graphs outperform many commonly used self-balancing trees.

Słowa kluczowe

EN

self balancing trees; self sorting trees; self aggregating data structures; associative structures; data access efficiency; representation of relationships

• Wydawca: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2020
• Tom: Vol. 30, no. 4
• Strony: 717--731
• Opis fizyczny: Bibliogr. 39 poz., rys., tab.

Twórcy

autor

Horzyk Adrian

• Department of Biocybernetics and Biomedical Engineering, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland

autor

Bulanda Daniel

• Department of Biocybernetics and Biomedical Engineering, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland

autor

Starzyk Janusz A.

• Faculty of Applied Computer Science, University of Information Technology and Management in Rzeszów, ul. Sucharskiego 2, 35-225 Rzeszów, Poland; School of Electrical Engineering and Computer Science, Ohio University, Athens, OH 45701, USA

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