<abstract xmlns="http://www.w3.org/1999/xhtml"><p>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.</p></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.

Ant–Based Clustering for Flow Graph Mining

University of Information Technology and Management in Rzeszów

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Ant\u2013Based Clustering for Flow Graph Mining"}

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...

Ant–Based Clustering for Flow Graph Mining

Publié en ligne: 29 sept. 2020

Pages: 561 - 572

Reçu: 21 nov. 2019

Accepté: 08 juin 2020

DOI: https://doi.org/10.34768/amcs-2020-0041

Mots clés
possibly certain sequences, flow graphs, rough sets, fuzzy sets, ant-based clustering

© 2020 Arkadiusz Lewicki et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Ant–Based Clustering for Flow Graph Mining

Publié en ligne: 29 sept. 2020

Pages: 561 - 572

Reçu: 21 nov. 2019

Accepté: 08 juin 2020

DOI: https://doi.org/10.34768/amcs-2020-0041

Mots cléspossibly certain sequences, flow graphs, rough sets, fuzzy sets, ant-based clustering

© 2020 Arkadiusz Lewicki et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
possibly certain sequences, flow graphs, rough sets, fuzzy sets, ant-based clustering