research-article

SimClusters: Community-Based Representations for Heterogeneous Recommendations at Twitter

Authors:

Jerry Jiang, and

Jimmy LinAuthors Info & Claims

KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

August 2020

Pages 3183 - 3193

https://doi.org/10.1145/3394486.3403370

Published: 20 August 2020 Publication History

Abstract

Personalized recommendation products at Twitter target a multitude of heterogeneous items: Tweets, Events, Topics, Hashtags, and users. Each of these targets varies in their cardinality (which affects the scale of the problem) and their "shelf life'' (which constrains the latency of generating the recommendations). Although Twitter has built a variety of recommendation systems before dating back a decade, solutions to the broader problem were mostly tackled piecemeal. In this paper, we present SimClusters, a general-purpose representation layer based on overlapping communities into which users as well as heterogeneous content can be captured as sparse, interpretable vectors to support a multitude of recommendation tasks. We propose a novel algorithm for community discovery based on Metropolis-Hastings sampling, which is both more accurate and significantly faster than off-the-shelf alternatives. SimClusters scales to networks with billions of users and has been effective across a variety of deployed applications at Twitter.

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Cited By

Liu XWu YFiumara GDe Meo P(2024)Heterogeneous graph community detection method based on K-nearest neighbor graph neural networkIntelligent Data Analysis10.3233/IDA-230356(1-22)Online publication date: 21-Mar-2024
https://doi.org/10.3233/IDA-230356
Santos GLakhotia KDe Rose C(2024)Towards a Scalable Parallel Infomap Algorithm for Community Detection2024 32nd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)10.1109/PDP62718.2024.00023(116-123)Online publication date: 20-Mar-2024
https://doi.org/10.1109/PDP62718.2024.00023
Zhao QMiao YAn DLian JLi M(2024)HGNN-QSSA: Heterogeneous Graph Neural Networks With Quantitative Sampling and Structure-Aware AttentionIEEE Access10.1109/ACCESS.2024.336623112(25512-25524)Online publication date: 2024
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Index Terms

SimClusters: Community-Based Representations for Heterogeneous Recommendations at Twitter
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems

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cover image ACM Conferences

KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining

August 2020

3664 pages

ISBN:9781450379984

DOI:10.1145/3394486

General Chairs:
Rajesh Gupta
UC San Diego, USA
,
Yan Liu
USC, USA
,
Program Chairs:
Mohak Shah
LG Electronics, USA
,
Suju Rajan
Linkedin, USA
,
Publications Chairs:
Jiliang Tang
Michigan State, USA
,
B. Aditya Prakash
Georgia Tech, USA

Copyright © 2020 ACM.

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Published: 20 August 2020

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July 6 - 10, 2020

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

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https://doi.org/10.3233/IDA-230356
Santos GLakhotia KDe Rose C(2024)Towards a Scalable Parallel Infomap Algorithm for Community Detection2024 32nd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)10.1109/PDP62718.2024.00023(116-123)Online publication date: 20-Mar-2024
https://doi.org/10.1109/PDP62718.2024.00023
Zhao QMiao YAn DLian JLi M(2024)HGNN-QSSA: Heterogeneous Graph Neural Networks With Quantitative Sampling and Structure-Aware AttentionIEEE Access10.1109/ACCESS.2024.336623112(25512-25524)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3366231
Bouchaud P(2024)Skewed perspectives: examining the influence of engagement maximization on content diversity in social media feedsJournal of Computational Social Science10.1007/s42001-024-00255-wOnline publication date: 20-Mar-2024
https://doi.org/10.1007/s42001-024-00255-w
Lounnas BBenazi MKamel M(2024)A robust two-step algorithm for community detection based on node similarityThe Journal of Supercomputing10.1007/s11227-024-06328-xOnline publication date: 3-Jul-2024
https://doi.org/10.1007/s11227-024-06328-x
Emeric AVictor C(2024)Interpretable Cross-Platform Coordination Detection on Social NetworksComplex Networks & Their Applications XII10.1007/978-3-031-53503-1_12(143-155)Online publication date: 29-Feb-2024
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Thorburn LPolukarov MVentre CElkind E(2023)Error in the Euclidean preference modelProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/322(2888-2896)Online publication date: 19-Aug-2023
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Jiang WHe HLin LTang QWang R(2023)Counterfactual Reasoning Over Community Detection: A Case Study of the Public Science Day CommunityJournal of Social Computing10.23919/JSC.2023.00104:2(125-138)Online publication date: Jun-2023
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Gamal MMohamed HEl-Maddah I(2023)Multi-Modal Graph-Based Recommendation System: Integrating Heterogeneous Modalities for Enhanced Predictions2023 International Conference on Electrical, Computer and Energy Technologies (ICECET)10.1109/ICECET58911.2023.10389370(1-9)Online publication date: 16-Nov-2023
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Mu CHuang HFang YLiu Y(2023)A Graph Convolutional Neural Network for Recommendation Based on Community Detection and Combination of Multiple Heterogeneous Graphs2023 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM58522.2023.00154(1235-1240)Online publication date: 1-Dec-2023
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