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Computational Data and Social Networks

10th International Conference, CSoNet 2021, Virtual Event, November 15–17, 2021, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. David Mohaisen

    1. University of Central Florida, Orlando, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Ruoming Jin

    1. Kent State University, Kent, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13116)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: CSoNet 2021.

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Table of contents (33 papers)

  1. Front Matter

    Pages i-xi
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  2. Combinatorial Optimization and Learning

    1. Front Matter

      Pages 1-1
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    2. Streaming Algorithms for Maximizing Non-submodular Functions on the Integer Lattice

      • Bin Liu, Zihan Chen, Huijuan Wang, Weili Wu
      Pages 3-14

    3. Causal Inference for Influence Propagation—Identifiability of the Independent Cascade Model

      • Shi Feng, Wei Chen
      Pages 15-26

    4. Streaming Algorithms for Budgeted k-Submodular Maximization Problem

      • Canh V. Pham, Quang C. Vu, Dung K. T. Ha, Tai T. Nguyen
      Pages 27-38

    5. Approximation Algorithms for the Lower Bounded Correlation Clustering Problem

      • Sai Ji, Yinhong Dong, Donglei Du, Dachuan Xu
      Pages 39-49

    6. Approximation Algorithm for Maximizing Nonnegative Weakly Monotonic Set Functions

      • Min Cui, Donglei Du, Dachuan Xu, Ruiqi Yang
      Pages 50-58

    7. Differentially Private Submodular Maximization over Integer Lattice

      • Jiaming Hu, Dachuan Xu, Donglei Du, Cuixia Miao
      Pages 59-67

    8. Maximizing the Sum of a Supermodular Function and a Monotone DR-submodular Function Subject to a Knapsack Constraint on the Integer Lattice

      • Jingjing Tan, Yicheng Xu, Dongmei Zhang, Xiaoqing Zhang
      Pages 68-75

  3. Deep Learning and Applications to Complex and Social Systems

    1. Front Matter

      Pages 77-77
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    2. A Framework for Accelerating Graph Convolutional Networks on Massive Datasets

      • Xiang Li, Ruoming Jin, Rajiv Ramnath, Gagan Agrawal
      Pages 79-92

    3. AdvEdge: Optimizing Adversarial Perturbations Against Interpretable Deep Learning

      • Eldor Abdukhamidov, Mohammed Abuhamad, Firuz Juraev, Eric Chan-Tin, Tamer AbuHmed
      Pages 93-105

    4. Incorporating Transformer Models for Sentiment Analysis and News Classification in Khmer

      • Md Rifatul Islam Rifat, Abdullah Al Imran
      Pages 106-117

    5. Deep Bangla Authorship Attribution Using Transformer Models

      • Abdullah Al Imran, Md Nur Amin
      Pages 118-128

    6. A Deep Learning Based Traffic Sign Detection for Intelligent Transportation Systems

      • Bao-Long Le, Gia-Huy Lam, Xuan-Vinh Nguyen, The-Manh Nguyen, Quoc-Loc Duong, Quang Dieu Tran et al.
      Pages 129-137

    7. Detecting Hate Speech Contents Using Embedding Models

      • Phuc H. Duong, Cuong C. Chung, Loc T. Vo, Hien T. Nguyen, Dat Ngo
      Pages 138-146

    8. MIC Model for Cervical Cancer Risk Factors Deep Association Analysis

      • Tiehua Zhou, Yingxuan Tang, Ling Gong, Hua Xie, Minglei Shan, Ling Wang
      Pages 147-155

    9. Power Grid Cascading Failure Prediction Based on Transformer

      • Tianxin Zhou, Xiang Li, Haibing Lu
      Pages 156-167

  4. Measurements of Insight from Data

    1. Front Matter

      Pages 169-169
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    2. Security Breaches in the Healthcare Domain: A Spatiotemporal Analysis

      • Mohammed Al Kinoon, Marwan Omar, Manar Mohaisen, David Mohaisen
      Pages 171-183
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Keywords

About this book

This book constitutes the refereed proceedings of the 10th International Conference on Computational Data and Social Networks, CSoNet 2021, which was held online during November 15-17, 2021. The conference was initially planned to take place in Montreal, Quebec, Canada, but changed to an online event due to the COVID-19 pandemic. 

The 24 full and 8 short papers included in this book were carefully reviewed and selected from 57 submissions. They were organized in topical sections as follows: Combinatorial optimization and learning; deep learning and applications to complex and social systems; measurements of insight from data; complex networks analytics; special track on fact-checking, fake news and malware detection in online social networks; and special track on information spread in social and data networks.

 

Editors and Affiliations

  • University of Central Florida, Orlando, USA

    David Mohaisen

  • Kent State University, Kent, USA

    Ruoming Jin

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