Ferdowsi, A. (2022). An Integer Programming Approach Reinforced by a Message-passing Procedure for Detecting Dense Attributed Subgraphs. In M. Ganzha, L. Maciaszek, M. Paprzycki, & D. Ślęzak (Eds.), Proceedings of the 17th Conference on Computer Science and Intelligence Systems (pp. 569–576). https://doi.org/10.15439/2022F64
E191-02 - Forschungsbereich Embedded Computing Systems
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Published in:
Proceedings of the 17th Conference on Computer Science and Intelligence Systems
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ISBN:
978-83-962423-9-6
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Volume:
30
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Date (published):
2022
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Event name:
17th Conference on Computer Science and Intelligence Systems (FedCSIS 2022)
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Event date:
4-Sep-2022 - 7-Sep-2022
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Event place:
Sofia, Bulgaria
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Number of Pages:
8
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Peer reviewed:
Yes
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Keywords:
Graph partitioning; Integer programming; Local search; Message passing; Network analysis
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Abstract:
One of the recent challenging but vital tasks in graph theory and network analysis, especially when dealing with graphs equipped with a set of nodal attributes, is to discover subgraphs consisting of highly interacting nodes with respect to the number of edges and the attributes' similarities. This paper proposes an approach based on integer programming modeling and the graph neural network message-passing manner for efficiently extracting these subgraphs. The experiments illustrate the proposed method's privilege over some alternative algorithms known so far, utilizing several well-known instances.
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Research Areas:
Computer Engineering and Software-Intensive Systems: 100%
