Advances in Knowledge Discovery and Data Mining

6th Pacific-Asia Conference, PAKDD 2002 Taipei, Taiwan, May 6–8, 2002 Proceedings

  • Ming-Syan Chen
  • Philip S. Yu
  • Bing Liu

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2336)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 2336)

Table of contents

  1. Front Matter
    Pages I-XIII
  2. Industrial Papers (Invited)

  3. Survey Papers (Invited)

    1. Jaideep Srivastava, Jau-Hwang Wang, Ee-Peng Lim, San-Yih Hwang
      Pages 14-27
    2. Osmar R. Zaïane, Andrew Foss, Chi-Hoon Lee, Weinan Wang
      Pages 28-39
  4. Association Rules (I)

    1. Jacinto Mata, José-Luis Alvarez, José-Cristobal Riquelme
      Pages 40-51
    2. Jochen Hipp, Christoph Mangold, Ulrich Güntzer, Gholamreza Nakhaeizadeh
      Pages 52-65
    3. Qin Ding, Qiang Ding, William Perrizo
      Pages 66-79
    4. Vikram Pudi, Jayant R. Haritsa
      Pages 80-91
  5. Classification (I)

    1. Jung-Yi Lin, Been-Chian Chien, Tzung-Pei Hong
      Pages 92-103
    2. Zhipeng Xie, Wynne Hsu, Zongtian Liu, Mong Li Lee
      Pages 104-114
    3. Lili Diao, Keyun Hu, Yuchang Lu, Chunyi Shi
      Pages 115-122
    4. Charles X. Ling, Huajie Zhang
      Pages 123-134
  6. Interestingness

  7. Sequence Mining

    1. Minghua Zhang, Ben Kao, David Cheung, Chi-Lap Yip
      Pages 186-197

Other volumes

  1. Advances in Knowledge Discovery and Data Mining
    6th Pacific-Asia Conference, PAKDD 2002 Taipei, Taiwan, May 6–8, 2002 Proceedings
  2. KDD Workshop MDM/KDD 2002. PAKDD Workshop KDMCD 2002. Revised Papers

About these proceedings

Introduction

Knowledge discovery and data mining have become areas of growing significance because of the recent increasing demand for KDD techniques, including those used in machine learning, databases, statistics, knowledge acquisition, data visualization, and high performance computing. In view of this, and following the success of the five previous PAKDD conferences, the sixth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2002) aimed to provide a forum for the sharing of original research results, innovative ideas, state-of-the-art developments, and implementation experiences in knowledge discovery and data mining among researchers in academic and industrial organizations. Much work went into preparing a program of high quality. We received 128 submissions. Every paper was reviewed by 3 program committee members, and 32 were selected as regular papers and 20 were selected as short papers, representing a 25% acceptance rate for regular papers. The PAKDD 2002 program was further enhanced by two keynote speeches, delivered by Vipin Kumar from the Univ. of Minnesota and Rajeev Rastogi from AT&T. In addition, PAKDD 2002 was complemented by three tutorials, XML and data mining (by Kyuseok Shim and Surajit Chadhuri), mining customer data across various customer touchpoints at- commerce sites (by Jaideep Srivastava), and data clustering analysis, from simple groupings to scalable clustering with constraints (by Osmar Zaiane and Andrew Foss).

Keywords

classification clustering data mining data warehouse knowledge knowledge discovery web mining

Editors and affiliations

  • Ming-Syan Chen
    • 1
  • Philip S. Yu
    • 2
  • Bing Liu
    • 3
  1. 1.EE DepartmentNational Taiwan UniversityTaipeiTaiwan, ROC
  2. 2.IBM Thomas J. Watson Research CenterHawthorneUSA
  3. 3.School of ComputingNational University of SingaporeSingapore

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-47887-6
  • Copyright Information Springer-Verlag Berlin Heidelberg 2002
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-43704-8
  • Online ISBN 978-3-540-47887-4
  • Series Print ISSN 0302-9743
  • About this book