Author Identifier (ORCID)

Jianxin Li: https://orcid.org/0000-0002-9059-330X

Abstract

Community search in heterogeneous information networks (HINs) often neglects temporal dynamics, yielding structures that poorly reflect real-world interactions. We introduce the Temporal HIN Community Search (THCS) problem and propose a novel core model that captures both structural cohesiveness and temporal relevance. Our model uses a time span constraint to ensure interaction recency and a query interval for flexible temporal exploration, filtering irrelevant connections while preserving structural density. We develop two efficient online algorithms—Center-based Sliding Window search and Incremental Center Expansion—that exploit meta-path symmetry and dynamic connectivity tracking. For frequent queries, we design a Temporal HIN Core Interval-Index (TCI-Index), organising minimal core intervals hierarchically with innovative compression techniques. Experiments on real-world datasets show our methods significantly outperform baselines, finding temporally meaningful communities with high efficiency.

Keywords

temporal networks, heterogeneous information networks, community search, dynamic graph algorithms, meta-paths, temporal indexing

Document Type

Conference Proceeding

Date of Publication

1-1-2025

Location of the Work

Boston, United States

Volume

18

Issue

13

Publication Title

Proceedings of the VLDB Endowment

Publisher

Association for Computing Machinery

School

School of Business and Law

RAS ID

93729

Funding Information

This research was jointly supported by ARC Discovery and DECRA Projects under Grant No. DP250100536, DP220102191, DP240101591 and DE240100200.

Australian Research Council (ARC)

1

ECU as administrating institution

1

Grant Number

ARC Numbers : DP250100536, DP220102191, DP240101591, DE240100200

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Event Title

52nd International Conference on Very Large Data Bases

Event Dates

31 August 2025 - 04 September 2026

Comments

Tang, Y., Liu, C., Chen, L., Zhou, R., & Li, J. (2025). Finding time-proximity communities in temporal heterogeneous information networks. Proceedings of the VLDB Endowment, 18(13), 5740-5752. https://doi.org/10.14778/3773731.3773747

First Page

5740

Last Page

5752

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Link to publisher version (DOI)

10.14778/3773731.3773747