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Finding Densest Subgraphs with Edge-Color Constraints
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Theoretical Computer Science, TCS.ORCID iD: 0000-0002-2526-8762
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Theoretical Computer Science, TCS.
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Theoretical Computer Science, TCS.ORCID iD: 0000-0002-5211-112X
2024 (English)In: WWW 2024 - Proceedings of the ACM Web Conference, Association for Computing Machinery (ACM) , 2024, p. 936-947Conference paper, Published paper (Refereed)
Abstract [en]

We consider a variant of the densest subgraph problem in networks with single or multiple edge attributes. For example, in a social network, the edge attributes may describe the type of relationship between users, such as friends, family, or acquaintances, or different types of communication. For conceptual simplicity, we view the attributes as edge colors. The new problem we address is to find a diverse densest subgraph that fulfills given requirements on the numbers of edges of specific colors. When searching for a dense social network community, our problem will enforce the requirement that the community is diverse according to criteria specified by the edge attributes. We show that the decision versions for finding exactly, at most, and at least h colored edges densest subgraph, where h is a vector of color requirements, are NP-complete, for already two colors. For the problem of finding a densest subgraph with at least h colored edges, we provide a linear-time constant-factor approximation algorithm when the input graph is sparse. On the way, we introduce the related at least h (non-colored) edges densest subgraph problem, show its hardness, and also provide a linear-time constant-factor approximation. In our experiments, we demonstrate the efficacy and efficiency of our new algorithms.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM) , 2024. p. 936-947
Keywords [en]
densest subgraph, density, diversity, social networks
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-347330DOI: 10.1145/3589334.3645647Scopus ID: 2-s2.0-85194105710OAI: oai:DiVA.org:kth-347330DiVA, id: diva2:1867263
Conference
33rd ACM Web Conference, WWW 2024, Singapore, Singapore, May 13 2024 - May 17 2024
Note

Part of ISBN [9798400701719]QC 20240612

Available from: 2024-06-10 Created: 2024-06-10 Last updated: 2024-12-03Bibliographically approved

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Oettershagen, LutzWang, HongliangGionis, Aristides

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