HyperGraph Convolution Based Attributed HyperGraph Clustering

Barakeel Fanseu Kamhoua, Lin Zhang, Kaili Ma, James Sheung Chak Cheng, Bo Li, Bo Han

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

Attributed Graph Clustering (AGC) and Attributed Hypergraph Clustering (AHC) are important topics in graph mining with many applications. For AGC, amongst the unsupervised methods that combine the graph structure with node attributes, graph convolution has been shown to achieve impressive results. However, the effects of graph convolution on AGC have not yet been adequately studied. In this paper, we show that graph convolution attempts to find the best trade-off between node attribute distance and the number of inter-cluster edges. On the one hand, we show that compared to clustering node attributes directly, graph convolution produces a greater distance between node attributes in the same cluster and a smaller distance between node attributes in different clusters (which is detrimental for clustering). On the other hand, we show that graph convolution benefits clustering by considerably reducing the number of edges among different clusters. We then extend our result on AGC to AHC and leverage the hypergraph convolution to propose an unsupervised, fast, and memory-efficient algorithm (GRAC) for AHC, which achieves excellent performance on popular supervised clustering measures.

Original languageEnglish
Title of host publicationCIKM '21: Proceedings of the 30th ACM International Conference on Information & Knowledge Management
PublisherAssociation for Computing Machinery (ACM)
Pages453-463
Number of pages11
ISBN (Print)9781450384469
DOIs
Publication statusPublished - 26 Oct 2021
Event30th ACM International Conference on Information and Knowledge Management, CIKM 2021 - Virtual, Online, Gold Coast, Queensland, Australia
Duration: 1 Nov 20215 Nov 2021
https://www.cikm2021.org/
https://dl.acm.org/doi/proceedings/10.1145/3459637

Publication series

NameProceedings of International Conference on Information and Knowledge Management

Conference

Conference30th ACM International Conference on Information and Knowledge Management, CIKM 2021
Country/TerritoryAustralia
CityGold Coast, Queensland
Period1/11/215/11/21
Internet address

Scopus Subject Areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

User-Defined Keywords

  • (hyper)graph convolution
  • attributed (hyper)graph clustering

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