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Advances in Knowledge Discovery and Data Mining, Part I

16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June1, 2012, Proceedings, Part I

  • Conference proceedings
  • © 2012

Overview

Editors:
  1. Pang-Ning Tan

    1. Department of Computer Science, Michigan State University, East Lansing, USA

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  2. Sanjay Chawla

    1. School of Information Technologies, University of Sydney, Sydney, Australia

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  3. Chin Kuan Ho

    1. Faculty of Computing and Informatics, Jalan Multimedia, Multimedia University, Cyberjaya, Malaysia

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  4. James Bailey

    1. Department of Computing and Information Systems, The University of Melbourne, Melbourne, Australia

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 7301)

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

Included in the following conference series:

Conference proceedings info: PAKDD 2012.

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Table of contents (50 papers)

  1. Supervised Learning: Active, Ensemble, Rare-Class and Online

    1. Active Learning with c-Certainty

      • Eileen A. Ni, Charles X. Ling
      Pages 231-242

    2. A Term Association Translation Model for Naive Bayes Text Classification

      • Meng-Sung Wu, Hsin-Min Wang
      Pages 243-253

    3. A Double-Ensemble Approach for Classifying Skewed Data Streams

      • Chongsheng Zhang, Paolo Soda
      Pages 254-265

    4. Generating Balanced Classifier-Independent Training Samples from Unlabeled Data

      • Youngja Park, Zijie Qi, Suresh N. Chari, Ian M. Molloy
      Pages 266-281

    5. Nyström Approximate Model Selection for LSSVM

      • Lizhong Ding, Shizhong Liao
      Pages 282-293

    6. Exploiting Label Dependency for Hierarchical Multi-label Classification

      • Noor Alaydie, Chandan K. Reddy, Farshad Fotouhi
      Pages 294-305

    7. Diversity Analysis on Boosting Nominal Concepts

      • Nida Meddouri, Héla Khoufi, Mondher Sadok Maddouri
      Pages 306-317

    8. Extreme Value Prediction for Zero-Inflated Data

      • Fan Xin, Zubin Abraham
      Pages 318-329

    9. Learning to Diversify Expert Finding with Subtopics

      • Hang Su, Jie Tang, Wanling Hong
      Pages 330-341

    10. An Associative Classifier for Uncertain Datasets

      • Metanat Hooshsadat, Osmar R. Zaïane
      Pages 342-353

  2. Unsupervised Learning: Clustering, Probabilistic Modeling

    1. Neighborhood-Based Smoothing of External Cluster Validity Measures

      • Ken-ichi Fukui, Masayuki Numao
      Pages 354-365

    2. Sequential Entity Group Topic Model for Getting Topic Flows of Entity Groups within One Document

      • Young-Seob Jeong, Ho-Jin Choi
      Pages 366-378

    3. Topological Comparisons of Proximity Measures

      • Djamel Abdelkader Zighed, Rafik Abdesselam, Asmelash Hadgu
      Pages 379-391

    4. Quad-tuple PLSA: Incorporating Entity and Its Rating in Aspect Identification

      • Wenjuan Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi
      Pages 392-404

    5. Clustering-Based k-Anonymity

      • Xianmang He, HuaHui Chen, Yefang Chen, Yihong Dong, Peng Wang, Zhenhua Huang
      Pages 405-417

    6. Unsupervised Ensemble Learning for Mining Top-n Outliers

      • Jun Gao, Weiming Hu, Zhongfei(Mark) Zhang, Ou Wu
      Pages 418-430

    7. Towards Personalized Context-Aware Recommendation by Mining Context Logs through Topic Models

      • Kuifei Yu, Baoxian Zhang, Hengshu Zhu, Huanhuan Cao, Jilei Tian
      Pages 431-443

    8. Mining of Temporal Coherent Subspace Clusters in Multivariate Time Series Databases

      • Hardy Kremer, Stephan Günnemann, Arne Held, Thomas Seidl
      Pages 444-455

    9. A Vertex Similarity Probability Model for Finding Network Community Structure

      • Kan Li, Yin Pang
      Pages 456-467

    10. Hybrid-ε-greedy for Mobile Context-Aware Recommender System

      • Djallel Bouneffouf, Amel Bouzeghoub, Alda Lopes Gançarski
      Pages 468-479
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Other volumes

  1. Advances in Knowledge Discovery and Data Mining

  2. Advances in Knowledge Discovery and Data Mining

  3. Emerging Trends in Knowledge Discovery and Data Mining

Keywords

About this book

The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.

Editors and Affiliations

  • Department of Computer Science, Michigan State University, East Lansing, USA

    Pang-Ning Tan

  • School of Information Technologies, University of Sydney, Sydney, Australia

    Sanjay Chawla

  • Faculty of Computing and Informatics, Jalan Multimedia, Multimedia University, Cyberjaya, Malaysia

    Chin Kuan Ho

  • Department of Computing and Information Systems, The University of Melbourne, Melbourne, Australia

    James Bailey

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