Converting network-unlike data into complex networks: Problems and prospective

A. A. Tikhomirov, O. G. Berestneva, E. Mokina, N. Kinash, M. Kuklina, A. I. Trufanov, A. Rossodivita, V. Kuklina, I. Bilichenko, V. Bogdanov

Research output: Contribution to journalConference articlepeer-review

Abstract

Often network science with complex networks as its basic entity has attracted scientific societies with their diverse practical capacities. Some entities (objects, processes, and data) having their built-in web nature might be considered as networks seamlessly. Contrary, network mapping for Network-Unlike Data (NUD), i.e. images and time series, is extremely complicated and manifold, so that explorers face with a tough problem which converting algorithm they should apply. We put in central focus separating data properties in line with their scale diversity-in distance, time, and nature and suggested a three step algorithm (scale-based one) to map NUD into complex networks. The algorithm was applied to networkalize two types of geographic maps of Olkhon district, Baikal Natural Territory, Irkutsk region, Russian Federation. It was underlined that the algorithm models coarse-graining and area-like linking and forms thoroughly output structures of really complex topologies with intrinsic scale-free and small world properties. In addition to simple examples transformation of NUD into multiplex networks is considered as a promising approach to study more complex systems of the real world. Networkalization concerned challenges in extracting the pertinent information from huge data resources conveyed by a network imprint for each file is also discussed.

Original languageEnglish
Article number012015
JournalJournal of Physics: Conference Series
Volume1661
Issue number1
DOIs
Publication statusPublished - 10 Nov 2020
Event2020 International Conference on Information Technology in Business and Industry, ITBI 2020 - Novosibirsk, Russian Federation
Duration: 6 Apr 20208 Apr 2020

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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