short-paper

Collaborative Social Group Influence for Event Recommendation

Authors:

Li Gao,

Jia Wu,

Zhi Qiao,

Chuan Zhou,

Hong Yang,

Yue HuAuthors Info & Claims

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

Pages 1941 - 1944

https://doi.org/10.1145/2983323.2983879

Published: 24 October 2016 Publication History

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Abstract

In event-based social networks, such as Meetup, social groups refer to self-organized communities that consist of users who share the same interests. In many real-world scenarios, users usually have social group preference and join interested social groups to attend events. It is therefore necessary to consider the influence of social groups to improve the event recommendation performance; however, existing event recommendation models generally consider users' individual preferences and neglect the influence of social groups. To this end, we propose a new Bayesian latent factor model SogBmf that combines social group influence and individual preference for event recommendation. Experiments on real-world data sets demonstrate the effectiveness of the proposed method.

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Cited By

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Xu JYang CKang X(2025)LAAP: Learning the Argument of An Entity with Event Prompts for document-level event extractionNeurocomputing10.1016/j.neucom.2024.128584613(128584)Online publication date: Jan-2025
https://doi.org/10.1016/j.neucom.2024.128584
Tao ZWang CTian ZXu KGuo YLi SBai YXie D(2024)SIAT: Document-level Event Extraction via Spatiality-Augmented Interaction Model with Adaptive ThresholdingACM Transactions on Asian and Low-Resource Language Information Processing10.1145/369826123:10(1-21)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3698261
Han JTang YTao QXia YZhang L(2024)Dual Homogeneity Hypergraph Motifs with Cross-view Contrastive Learning for Multiple Social RecommendationsACM Transactions on Knowledge Discovery from Data10.1145/365397618:6(1-24)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3653976
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Index Terms

Collaborative Social Group Influence for Event Recommendation
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Social recommendation
2. Information systems
  1. Information systems applications
    1. Data mining

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Information & Contributors

Information

Published In

CIKM '16: Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

October 2016

2566 pages

ISBN:9781450340731

DOI:10.1145/2983323

General Chairs:
Snehasis Mukhopadhyay
Indiana University Purdue University Indianapolis, USA
,
ChengXiang Zhai
University of Illinois at Urbana-Champaign, USA
,
Program Chairs:
Elisa Bertino
Purdue University
,
Fabio Crestani
University of Lugano
,
Javed Mostafa
University of North Carolina
,
Jie Tang
Tsinghua University
,
Luo Si
Alibaba Group Inc & Purdue University
,
Xiaofang Zhou
University of Queensland
,
Yi Chang
Yahoo Research
,
Yunyao Li
IBM Research - Almaden
,
Parikshit Sondhi
WalmartLabs

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Publication History

Published: 24 October 2016

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CIKM'16: ACM Conference on Information and Knowledge Management

October 24 - 28, 2016

Indiana, Indianapolis, USA

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CIKM '16 Paper Acceptance Rate 160 of 701 submissions, 23%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

View all

Xu JYang CKang X(2025)LAAP: Learning the Argument of An Entity with Event Prompts for document-level event extractionNeurocomputing10.1016/j.neucom.2024.128584613(128584)Online publication date: Jan-2025
https://doi.org/10.1016/j.neucom.2024.128584
Tao ZWang CTian ZXu KGuo YLi SBai YXie D(2024)SIAT: Document-level Event Extraction via Spatiality-Augmented Interaction Model with Adaptive ThresholdingACM Transactions on Asian and Low-Resource Language Information Processing10.1145/369826123:10(1-21)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3698261
Han JTang YTao QXia YZhang L(2024)Dual Homogeneity Hypergraph Motifs with Cross-view Contrastive Learning for Multiple Social RecommendationsACM Transactions on Knowledge Discovery from Data10.1145/365397618:6(1-24)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3653976
Wan QWan CXiao KXiong HLiu DLiu XHu R(2024)Token-Event-Role Structure-Based Multi-Channel Document-Level Event ExtractionACM Transactions on Information Systems10.1145/364388542:4(1-27)Online publication date: 7-Feb-2024
https://dl.acm.org/doi/10.1145/3643885
Yang ZWei YLi HLi QJiang LSun LYu XHu CPeng HSerra ESpezzano F(2024)Adaptive Differentially Private Structural Entropy Minimization for Unsupervised Social Event DetectionProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679537(2950-2960)Online publication date: 21-Oct-2024
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Li QLi JSheng JCui SWu JHei YPeng HGuo SWang LBeheshti AYu P(2024)A Survey on Deep Learning Event Extraction: Approaches and ApplicationsIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2022.321316835:5(6301-6321)Online publication date: May-2024
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Su XXue SLiu FWu JYang JZhou CHu WParis CNepal SJin DSheng QYu P(2024)A Comprehensive Survey on Community Detection With Deep LearningIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2021.3137396(1-21)Online publication date: 2024
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Li YTang YCheng JHe CTang F(2024)A Community Detection Method to Counter the Semantic Noise of Complex Networks: Bridging a Topology and Semantic Subspace TransformationIEEE Systems, Man, and Cybernetics Magazine10.1109/MSMC.2023.323616310:2(2-14)Online publication date: Apr-2024
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Zhang CLi GZhang H(2024)Multi-view contrastive learning with virtual social group influence for social recommendationKnowledge-Based Systems10.1016/j.knosys.2024.111751294(111751)Online publication date: Jun-2024
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Wang GZhou LGong JZhang X(2024)Heterogeneous Graph Neural Network with Hierarchical Attention for Group-Aware Paper Recommendation in Scientific Social NetworksApplied Soft Computing10.1016/j.asoc.2024.112448(112448)Online publication date: Nov-2024
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