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Advances in Knowledge Discovery and Data Mining

20th Pacific-Asia Conference, PAKDD 2016, Auckland, New Zealand, April 19-22, 2016, Proceedings, Part I

  • Conference proceedings
  • © 2016

Overview

Editors:
  1. James Bailey

    1. The University of Melbourne, Melbourne, Australia

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  2. Latifur Khan

    1. The University of Texas at Dallas, Richardson, USA

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  3. Takashi Washio

    1. Osaka University, Osaka, Japan

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  4. Gill Dobbie

    1. University of Auckland, Auckland, New Zealand

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  5. Joshua Zhexue Huang

    1. Shenzhen University, Shenzhen, China

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  6. Ruili Wang

    1. Massey University, Auckland, New Zealand

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9651)

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

Included in the following conference series:

Conference proceedings info: PAKDD 2016.

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Table of contents (47 papers)

  1. Front Matter

    Pages I-XXIV
    Download chapter PDF

  2. Classification

    1. Front Matter

      Pages 1-1
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    2. Joint Classification with Heterogeneous Labels Using Random Walk with Dynamic Label Propagation

      • Yongxin Liao, Shenxi Yuan, Jian Chen, Qingyao Wu, Bin Li
      Pages 3-13

    3. Hybrid Sampling with Bagging for Class Imbalance Learning

      • Yang Lu, Yiu-ming Cheung, Yuan Yan Tang
      Pages 14-26

    4. Sparse Adaptive Multi-hyperplane Machine

      • Khanh Nguyen, Trung Le, Vu Nguyen, Dinh Phung
      Pages 27-39

    5. Exploring Heterogeneous Product Networks for Discovering Collective Marketing Hyping Behavior

      • Qinzhe Zhang, Qin Zhang, Guodong Long, Peng Zhang, Chengqi Zhang
      Pages 40-51

    6. Optimal Training and Efficient Model Selection for Parameterized Large Margin Learning

      • Yuxun Zhou, Jae Yeon Baek, Dan Li, Costas J. Spanos
      Pages 52-64

    7. Locally Weighted Ensemble Learning for Regression

      • Man Yu, Zongxia Xie, Hong Shi, Qinghua Hu
      Pages 65-76

    8. Reliable Confidence Predictions Using Conformal Prediction

      • Henrik Linusson, Ulf Johansson, Henrik Boström, Tuve Löfström
      Pages 77-88

    9. Grade Prediction with Course and Student Specific Models

      • Agoritsa Polyzou, George Karypis
      Pages 89-101

    10. Flexible Transfer Learning Framework for Bayesian Optimisation

      • Tinu Theckel Joy, Santu Rana, Sunil Kumar Gupta, Svetha Venkatesh
      Pages 102-114

    11. A Simple Unlearning Framework for Online Learning Under Concept Drifts

      • Sheng-Chi You, Hsuan-Tien Lin
      Pages 115-126

    12. User-Guided Large Attributed Graph Clustering with Multiple Sparse Annotations

      • Jianping Cao, Senzhang Wang, Fengcai Qiao, Hui Wang, Feiyue Wang, Philip S. Yu
      Pages 127-138

    13. Early-Stage Event Prediction for Longitudinal Data

      • Mahtab J. Fard, Sanjay Chawla, Chandan K. Reddy
      Pages 139-151

    14. Toxicity Prediction in Cancer Using Multiple Instance Learning in a Multi-task Framework

      • Cheng Li, Sunil Gupta, Santu Rana, Wei Luo, Svetha Venkatesh, David Ashely et al.
      Pages 152-164

    15. Shot Boundary Detection Using Multi-instance Incremental and Decremental One-Class Support Vector Machine

      • Hanhe Lin, Jeremiah D. Deng, Brendon J. Woodford
      Pages 165-176

    16. Will I Win Your Favor? Predicting the Success of Altruistic Requests

      • Hsun-Ping Hsieh, Rui Yan, Cheng-Te Li
      Pages 177-188

  3. Feature Extraction and Pattern Mining

    1. Front Matter

      Pages 189-189
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    2. Unsupervised and Semi-supervised Dimensionality Reduction with Self-Organizing Incremental Neural Network and Graph Similarity Constraints

      • Zhiyang Xiang, Zhu Xiao, Yourong Huang, Dong Wang, Bin Fu, Wenjie Chen
      Pages 191-202

    3. Cross-View Feature Hashing for Image Retrieval

      • Wei Wu, Bin Li, Ling Chen, Chengqi Zhang
      Pages 203-214
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Other volumes

  1. Advances in Knowledge Discovery and Data Mining

  2. Advances in Knowledge Discovery and Data Mining

  3. Trends and Applications in Knowledge Discovery and Data Mining

Keywords

About this book

This two-volume set, LNAI 9651 and 9652, constitutes the thoroughly refereed proceedings of the 20th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2016, held in Auckland, New Zealand, in April 2016.

The 91 full papers were carefully reviewed and selected from 307 submissions. They are organized in topical sections named: classification; machine learning; applications; novel methods and algorithms; opinion mining and sentiment analysis; clustering; feature extraction and pattern mining; graph and network data; spatiotemporal and image data; anomaly detection and clustering; novel models and algorithms; and text mining and recommender systems.

Editors and Affiliations

  • The University of Melbourne, Melbourne, Australia

    James Bailey

  • The University of Texas at Dallas, Richardson, USA

    Latifur Khan

  • Osaka University, Osaka, Japan

    Takashi Washio

  • University of Auckland, Auckland, New Zealand

    Gill Dobbie

  • Shenzhen University, Shenzhen, China

    Joshua Zhexue Huang

  • Massey University, Auckland, New Zealand

    Ruili Wang

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