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  • Conference proceedings
  • © 2018

Advances in Knowledge Discovery and Data Mining

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

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)

Conference series link(s): PAKDD: Pacific-Asia Conference on Knowledge Discovery and Data Mining

Conference proceedings info: PAKDD 2018.

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Table of contents (64 papers)

  1. Front Matter

    Pages I-XXVIII
  2. Feature Learning and Data Mining Process

    1. Front Matter

      Pages 1-1
    2. A Scalable and Efficient Subgroup Blocking Scheme for Multidatabase Record Linkage

      • Thilina Ranbaduge, Dinusha Vatsalan, Peter Christen
      Pages 15-27
    3. Efficient Feature Selection Framework for Digital Marketing Applications

      • Wei Zhang, Shiladitya Bose, Said Kobeissi, Scott Tomko, Chris Challis
      Pages 28-39
    4. Feature Selection for Multiclass Binary Data

      • Kushani Perera, Jeffrey Chan, Shanika Karunasekera
      Pages 52-63
    5. Scalable Model-Based Cascaded Imputation of Missing Data

      • Jacob Montiel, Jesse Read, Albert Bifet, Talel Abdessalem
      Pages 64-76
    6. On Reducing Dimensionality of Labeled Data Efficiently

      • Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima
      Pages 77-88
    7. Using Metric Space Indexing for Complete and Efficient Record Linkage

      • Özgür Akgün, Alan Dearle, Graham Kirby, Peter Christen
      Pages 89-101
    8. Dimensionality Reduction via Community Detection in Small Sample Datasets

      • Kartikeya Bhardwaj, Radu Marculescu
      Pages 102-114
    9. An Interaction-Enhanced Feature Selection Algorithm

      • Xiaochuan Tang, Yuanshun Dai, Yanping Xiang, Liang Luo
      Pages 115-125
    10. An Extended Random-Sets Model for Fusion-Based Text Feature Selection

      • Abdullah Semran Alharbi, Yuefeng Li, Yue Xu
      Pages 126-138
    11. Efficient Approximate Algorithms for the Closest Pair Problem in High Dimensional Spaces

      • Xingyu Cai, Sanguthevar Rajasekaran, Fan Zhang
      Pages 151-163
    12. Efficient Compression Technique for Sparse Sets

      • Rameshwar Pratap, Ishan Sohony, Raghav Kulkarni
      Pages 164-176
  3. Community Detection and Network Science

    1. Front Matter

      Pages 191-191
    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

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.

 


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

Bibliographic Information

Buy it now

Buying options

Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access