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Advances in Knowledge Discovery and Data Mining

22nd Pacific-Asia Conference, PAKDD 2018, Melbourne, VIC, Australia, June 3-6, 2018, Proceedings, Part III

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Dinh Phung

    1. Deakin University, Geelong, Australia

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  2. Vincent S. Tseng

    1. National Chiao Tung University, Hsinchu City, Taiwan

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  3. Geoffrey I. Webb

    1. Monash University, Clayton, Australia

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  4. Bao Ho

    1. Japan Advanced Institute of Science and Technology, Nomi, Japan

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  5. Mohadeseh Ganji

    1. University of Melbourne, Melbourne, Australia

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  6. Lida Rashidi

    1. University of Melbourne, Melbourne, Australia

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 10939)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: PAKDD 2018.

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About this book

This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018.

The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications.

 


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Table of contents (64 papers)

  1. Front Matter

    Pages I-XXVIII
    Download chapter PDF

  2. Feature Learning and Data Mining Process

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Discovering High Utility Itemsets Based on the Artificial Bee Colony Algorithm

      • Wei Song, Chaomin Huang
      Pages 3-14

    3. A Scalable and Efficient Subgroup Blocking Scheme for Multidatabase Record Linkage

      • Thilina Ranbaduge, Dinusha Vatsalan, Peter Christen
      Pages 15-27

    4. Efficient Feature Selection Framework for Digital Marketing Applications

      • Wei Zhang, Shiladitya Bose, Said Kobeissi, Scott Tomko, Chris Challis
      Pages 28-39

    5. Dynamic Feature Selection Algorithm Based on Minimum Vertex Cover of Hypergraph

      • Xiaojun Xie, Xiaolin Qin
      Pages 40-51

    6. Feature Selection for Multiclass Binary Data

      • Kushani Perera, Jeffrey Chan, Shanika Karunasekera
      Pages 52-63

    7. Scalable Model-Based Cascaded Imputation of Missing Data

      • Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem
      Pages 64-76

    8. On Reducing Dimensionality of Labeled Data Efficiently

      • Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima
      Pages 77-88

    9. Using Metric Space Indexing for Complete and Efficient Record Linkage

      • Özgür Akgün, Alan Dearle, Graham Kirby, Peter Christen
      Pages 89-101

    10. Dimensionality Reduction via Community Detection in Small Sample Datasets

      • Kartikeya Bhardwaj, Radu Marculescu
      Pages 102-114

    11. An Interaction-Enhanced Feature Selection Algorithm

      • Xiaochuan Tang, Yuanshun Dai, Yanping Xiang, Liang Luo
      Pages 115-125

    12. An Extended Random-Sets Model for Fusion-Based Text Feature Selection

      • Abdullah Semran Alharbi, Yuefeng Li, Yue Xu
      Pages 126-138

    13. Attribute Reduction Algorithm Based on Improved Information Gain Rate and Ant Colony Optimization

      • Jipeng Wei, Qianjin Wei, Yimin Wen
      Pages 139-150

    14. Efficient Approximate Algorithms for the Closest Pair Problem in High Dimensional Spaces

      • Xingyu Cai, Sanguthevar Rajasekaran, Fan Zhang
      Pages 151-163

    15. Efficient Compression Technique for Sparse Sets

      • Rameshwar Pratap, Ishan Sohony, Raghav Kulkarni
      Pages 164-176

    16. It Pays to Be Certain: Unsupervised Record Linkage via Ambiguity Minimization

      • Anna Jurek, Deepak P.
      Pages 177-190

  3. Community Detection and Network Science

    1. Front Matter

      Pages 191-191
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    2. Consensus Community Detection in Multilayer Networks Using Parameter-Free Graph Pruning

      • Domenico Mandaglio, Alessia Amelio, Andrea Tagarelli
      Pages 193-205

    3. Community Discovery Based on Social Relations and Temporal-Spatial Topics in LBSNs

      • Shuai Xu, Jiuxin Cao, Xuelin Zhu, Yi Dong, Bo Liu
      Pages 206-217
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Other volumes

  1. Advances in Knowledge Discovery and Data Mining

  2. Advances in Knowledge Discovery and Data Mining

  3. Advances in Knowledge Discovery and Data Mining

  4. Trends and Applications in Knowledge Discovery and Data Mining

Editors and Affiliations

  • Deakin University, Geelong, Australia

    Dinh Phung

  • National Chiao Tung University, Hsinchu City, Taiwan

    Vincent S. Tseng

  • Monash University, Clayton, Australia

    Geoffrey I. Webb

  • Japan Advanced Institute of Science and Technology, Nomi, Japan

    Bao Ho

  • University of Melbourne, Melbourne, Australia

    Mohadeseh Ganji, Lida Rashidi

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