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Local Overlapping Spatial-aware Community Detection

Published: 12 January 2024 Publication History

Abstract

Local spatial-aware community detection refers to detecting a spatial-aware community for a given node using local information. A spatial-aware community means that nodes in the community are tightly connected in structure, and their locations are close to each other. Existing studies focus on detecting the local non-overlapping spatial-aware community, i.e., detecting a spatial-aware community containing the given node. However, many geosocial networks often contain overlapping spatial-aware communities. Therefore, we propose a local overlapping spatial-aware community detection (LOSCD) problem, which aims to detect all spatial-aware communities that contain a given node with local information. To address LOSCD problem, we design an algorithm based on Spatial Modularity and Edge Similarity, called SMES. SMES contains two processes: spatial expansion and structure detection. The spatial expansion process involves using spatial modularity to identify nodes that are spatially close, while the structural detection process employs edge similarity to identify nodes that are structurally close. Experimental results demonstrate that SMES outperforms comparison algorithms in terms of both structural and spatial cohesiveness.

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  • (2024)Budget-Constrained Ego Network Extraction With Maximized WillingnessIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.344616936:12(7692-7707)Online publication date: Dec-2024

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Published In

cover image ACM Transactions on Knowledge Discovery from Data
ACM Transactions on Knowledge Discovery from Data  Volume 18, Issue 3
April 2024
663 pages
EISSN:1556-472X
DOI:10.1145/3613567
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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 January 2024
Online AM: 27 November 2023
Accepted: 17 November 2023
Revised: 25 August 2023
Received: 16 April 2023
Published in TKDD Volume 18, Issue 3

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Author Tags

  1. Geosocial networks
  2. local community detection
  3. local spatial-aware community detection
  4. local overlapping spatial-aware community detection

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  • Research-article

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  • National Natural Science Foundation of China
  • Natural Science Foundation of Anhui Province of China

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  • (2024)Budget-Constrained Ego Network Extraction With Maximized WillingnessIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.344616936:12(7692-7707)Online publication date: Dec-2024

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