Creator:

Lewicki, Arkadiusz ; Pancerz, Krzysztof

Contributor:

Kołodziej, Joanna - ed. ; Pllana, Sabri - ed. ; Vitabile , Salvatore - ed.

Title:

Ant-based clustering for flow graph mining

Subtitle:

.

Group publication title:

AMCS, volume 30 (2020)

Subject and Keywords:

possibly certain sequences ; flow graphs ; rough sets ; fuzzy sets ; ant-based clustering

Abstract:

The paper is devoted to the problem of mining graph data. The goal of this process is to discover possibly certain sequences appearing in data. Both rough set flow graphs and fuzzy flow graphs are used to represent sequences of items originally arranged in tables representing information systems. Information systems are considered in the Pawlak sense, as knowledge representation systems. In the paper, an approach involving ant based clustering is proposed. We show that ant based clustering can be used not only for building possible large groups of similar objects, but also to build larger structures (in our case, sequences) of objects to obtain or preserve the desired properties.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Date:

2020

Resource Type:

artykuł

DOI:

10.34768/amcs-2020-0041

Pages:

561-572

Source:

AMCS, volume 30, number 3 (2020) ; click here to follow the link

Language:

eng

License CC BY 4.0:

click here to follow the link

Rights:

Biblioteka Uniwersytetu Zielonogórskiego