Autor:

Lewicki, Arkadiusz ; Pancerz, Krzysztof

Współtwórca:

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

Tytuł:

Ant-based clustering for flow graph mining

Podtytuł:

.

Tytuł publikacji grupowej:

AMCS, volume 30 (2020)

Temat i słowa kluczowe:

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.

Wydawca:

Zielona Góra: Uniwersytet Zielonogórski

Data wydania:

2020

Typ zasobu:

artykuł

DOI:

10.34768/amcs-2020-0041

Strony:

561-572

Źródło:

AMCS, volume 30, number 3 (2020) ; kliknij tutaj, żeby przejść

Jezyk:

eng

Licencja CC BY 4.0:

kliknij tutaj, żeby przejść

Prawa do dysponowania publikacją:

Biblioteka Uniwersytetu Zielonogórskiego