Awards

Each year the Steering Committee presents two special awards - The Most Influential Paper award (published 10 years ago) and the Most Distinguished Contribution award. The conference Program Committee also presents the best paper awards and the best student paper awards.


2005

Distinguished Contribution Award

Professor Hongjun Lu


2006

Distinguished Contribution Award

Professor Hiroshi Motoda

Most Influential Paper Award

Clustering Large Data Sets with Mixed Numeric and Categorical Values by Zhexue Huang. Proceedings of the 1st Pacific-Asia Conference on Knowledge Discovery and Data Mining, (PAKDD 1997), Singapore, World Scientific, 1997. Pages 21-35


2007

Distinguished Contribution Award

The 2007 award for most distinguished contribution went to Professor Ramamohanarao Kotagiri, FIEAust, FTSE, FAA, Professor, Department of Computer Science and Software Engineering, The University of Melbourne. Professor Kotagiri has a long and distinguished academic research career. He is well known for his pioneering work on hashing and information retrieval in database management, new techniques for intelligent, efficient and expressive database queries, the theory and practice of emerging patterns, intrusion detection and text mining. His publications have appeared in many highly regarded conferences and journals, including PAKDD, KDD, ICDM and PKDD, and IEEE TKDE, Data Mining and Knowledge Discovery, Machine Learning and Knowledge and Information Systems. He is a member of the Australian Academy of Science and also the Australian Academy of Technological Science and Engineering. He has also served on the Prime Minister’s Science and Engineering Innovation Council.

Most Influential Paper Award

Enhancing Effectiveness of Outlier Detections for Low Density Patterns, by Jian Tang, Zhixiang Chen, Ada Wai-Chee Fu, and David Wai-Lok Cheung. In Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, (PAKDD 2002), Lecture Notes In Computer Science, Vol 2035, Pages 247-259.


2008

Most Influential Paper Award

An Analysis of Quantitative Measures Associated with Rules by Yiyu Yao and Ning Zhong. Proceedings of the 3rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, (PAKDD 1999), Lecture Notes In Computer Science, Vol 1574, Springer, 1999


2009

Distinguished Contribution Award

The 2009 award for most distinguished contribution went to Professor David Cheung, Head of the Department of Computer Science and Director of the Center for E-Commerce Infrastructure Development, of the University of Hong Kong for his persistent outstanding contributions to PAKDD and eminent academic record. The citation for the award notes that Professor Cheung has been associated with the PAKDD Conference since it inception, serving on the steering committee since 2001 including a period as the chair of the steering committee. He was chair of the program committee of the fifth and ninth PAKDD conferences, in 2001 and 2005 and conference chair of PAKDD 2007. Professor Cheung has actively promoted the conference series in the Asia Pacific region and beyond and continues to encourage his own students and colleagues to contribute to the PAKDD series of conferences. Professor Cheung has a distinguished academic research career, introducing many new students to data mining and pushing forward the boundaries of research in data mining. His publications appear in many highly regarded conferences and journals. He and his students continue to support PAKKD as a conference of choice for presentation of esearch.

Most Influential Paper Award

Mining Access Patterns Efficiently from Web Logs by Jian Pei, Jiawei Han, Behzad Mortazavi-Asl, Hua Zhu. Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, (PAKDD 2000), Lecture Notes In Computer Science, Vol 1805, Springer, 2000


2010

Distinguished Contribution Award

The 2010 award for Most Distinguished Contribution went to Professor Masaru Kitsuregawa of the University of Tokyo. Masaru has been very active in his support and contribution to PAKDD over many years. He has served various roles in a number of PAKDD conferences, including as conference chair for 2000, 2009 and 2010, and program co-chair for 2006. He continues to provide guidance as a life member of the PAKDD Steering Committee. He is also a highly respected researcher in data mining and databases. He was a member of the VLDB Trustee during 1996-2002. He served as the co-general chair of IEEE ICDE 2005, held in Tokyo. He is serving as an Asian Coordinator of the IEEE Technical Committee on Data Engineering as well as chair of several well known database and data mining conferences. He is leading a large project named ‘Info-plosion’ in Japan. In 2009 he received the ACM SIGMOD E. F. Codd Innovation Award.

Most Influential Paper Award

Feature Selection for Clustering by Manoranjan Dash and Huan Liu. Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000), Lecture Notes In Computer Science, Vol 1805, Springer, 2000. Pages 110 - 121.

Best Paper Award

  • Best Paper Leman Akoglu, Mary McGlohon and Christos Faloutsos. OddBall: Spotting Anomalies in Weighted Graphs

  • Best Paper Runner Up Tao Yang, Longbing Cao and Chengqi Zhang. A Novel Prototype Reduction Method for the K-Nearest Neighbor Algorithm with K>=1

  • Best Student Paper Wanhong Xu. Supervising Latent Topic Model for Maximum-Margin Text Classification and Regression

  • Best Student Paper Runner Up Pallika Kanani, Andrew McCallum and Shaohan Hu. Resource-bounded Information Extraction: Acquiring Missing Feature Values On Demand


2011

Distinguished Contribution Award

The 2011 award for Most Distinguished Contribution went to Professor Graham Williams, Director and Senior Data Miner of the Australian Taxation Office, and Adjunct Professor, Australian National University, University of Canberra, and Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences. Graham is a key supporter of PAKDD and has made significant contribution to PAKDD since the inauguration of the conference. He has served in many roles in the PAKDD conference series. He has been the Steering Committee Co-Chair and Treasurer since 2001. He was the Organization Committee Chair of PAKDD 1998, Program Co-Chair of PAKDD 2001, Industrial Chair of PAKDD 2004 and the Tutorial Chair of PAKDD 2007. He is also the founder and Steering Committee Co-Chair of the Australasian Data Mining Conference series. Graham has made significant technical contributions with considerable success in the application of data mining technology to real world problems. His pivotal role in deploying data mining in industry was recognised by the Australian Taxation Office with an Innovation Award in 2006 and an Australia Day award in 2007. Graham has published extensively in data mining in many important conferences and journals. He is the author of the immensely popular open source Rattle data mining software and a keen advocate of freely sharing research software. His Internet book Data Mining Desktop Survival Guide is a highly popular tool book for data mining practitioners and this will be published shortly under the title Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discover, by Springer.

Most Influential Paper Award

Evaluation of Interestingness Measures for Ranking Discovered Knowledge by Robert J. Hilderman and Howard J. Hamilton. Lecture Notes In Computer Science, Vol 2035. Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2001. Pages 247 - 259. This paper introduced a new framework for considering how we measure the interestingness of discoveries, and has been adopted widely by other researchers.


2012

Distinguished Contribution Award

The 2012 award for Most Distinguished Contribution went to Professor Huan Liu of the Arizona State University, USA. Professor Liu has been involved in PAKDD from its beginnings in Singapore 16 years ago. He has been an active participant and, importantly, has helped guide PAKDD to ensure its ongoing quality and relevance to the international data mining community. The award also recognises his major research contributions over many years to knowledge discovery and data mining.


2013

Distinguished Contribution Award

The 2013 award for PAKDD Distinguished Contribution was awarded to Professor Jaideep Srivastava of the University of Minnesota, USA. This award recognises significant and ongoing contributions in research and services to the advancement of the PAKDD community and series of conferences. Professor Srivastava has been involved in PAKDD since PAKDD 2006 where he was the conference General Co-Chair. He has been an active supporter, contributing to the steering committee since then and has guided PAKDD administratively, and supported ongoing participation in the conference series. The award also recognises his major research contributions over many years to knowledge discovery and data mining. Congratulations to Professor Srivastava.


2014

Distinguished Contribution Award

The Distinguished Contributions Award is awarded to a member of our community to recognise and honour an individual who has made significant and continued contributions in research and services to the advancement of the PAKDD conferences. The selection committee for 2014 was chaired by Professor Jaideep Srivastava of the University of Minnesota, supported by Professors David Cheung of the University of Hong Kong and Masaru Kitsuregawa of Tokyo University.

The 2014 PAKDD Distinguished Contribution is awarded to Professor Kyu-Young Whang, a Distinguished Professor of the Korean Advanced Institute of Science and Technology. This award recognises significant and ongoing contributions in research and services to the advancement of the PAKDD community and series of conferences. Professor Whang has been involved in PAKDD since PAKDD 2003. He has been an active supporter, contributing to the steering committee since then and has guided PAKDD over the years to maintain a strong conference supporting data mining across the region. The award also recognises his major research contributions over many years to data engineering and data mining. Congratulations to Professor Whang.

Most Influential Paper Award

The Most Influential Paper Award is an award for a paper published at PAKDD tens years ago. The award recognises a paper that has had significant influence over the past decade. Google Scholar is used to identify a candidate pool of papers and these papers are then reviewed by the awards committee to consider the quality of citations. An important criteria is that the paper should present novel and big ideas which change our way of thinking. A challenger/champion approach is used by the awards committee to identify the most influential paper. The awards committee for 2014 was chaired by Professor Huan Liu, Arizona State University, USA, supported by Professor Joshua Huang of Shenzhen University, China, and Professor Thanaruk Theeramunkong, Thammasat University, Thailand.

The 2014 award for Most Influential Paper from PAKDD 2004 goes to Shantanu Godbole now of IBM India and Sunita Sarawagi of the Indian Institute of Technology, for their paper title Discriminative Methods for Multi-labeled Classification. The paper proposes to exploit the co-occurrence relationships of classes to label sets of documents, developing a new support vector machine ensemble to tackle the problem of multi-labelled text classification.

Best Paper Award

  • Best Research Paper Lei Duan, Guanting Tang, Jian Pei, James Bailey, Guozhu Dong, Akiko Campbell, and Changjie Tang: Mining Contrast Subspaces
  • Runner-Up Best Research Paper Yang Wang, Xuemin Lin, Qing Zhang, and Lin Wu: Shifting Hypergraphs by Probabilistic Voting
  • Best Application Paper Xiaofei Yang, Jiming Liu, William Kwok Wai Cheung, and Xiao-Nong Zhou: Inferring Metapopulation Based Disease Transmission Networks
  • Best Student Paper Tianqing Zhu, Gang Li, Wanlei Zhou, Ping Xiong, and Cao Yuan: Deferentially Private Tagging Recommendation based on Topic Model
  • Runner-Up Best Student Paper Miguel Araujo, Spiros Papadimitriou, Stephan Gunnemann, Christos Faloutsos, Prithwish Basu, Ananthram Swami, Evangelos E. Papalexakis, and Danai Koutra: Com2: Fast Automatic Discovery of Temporal (’Comet’) Communities


2015

Distinguished Contribution Award

The 2014 PAKDD Distinguished Contribution is awarded to Professor Kyu-Young Whang, a Distinguished Professor of the Korean Advanced Institute of Science and Technology. This award recognises significant and ongoing contributions in research and services to the advancement of the PAKDD community and series of conferences. Professor Whang has been involved in PAKDD since PAKDD 2003. He has been an active supporter, contributing to the steering committee since then and has guided PAKDD over the years to maintain a strong conference supporting data mining across the region. The award also recognises his major research contributions over many years to data engineering and data mining. Congratulations to Professor Whang.


2016

Distinguished Contribution Award

The Distinguished Contributions Award is awarded to a member of our community to recognise and honour an individual who has made significant and continued contributions in research and services to the advancement of the PAKDD conferences. The selection committee for 2016 was chaired by Professor David Cheung of the University of Hong Kong and assisted by Professors Kyu-Young Whang of the Korean Advanced Institute of Science & Technology and Chengqi Zhang of the University of Technology Sydney.

The 2016 PAKDD Distinguished Contribution is awarded to Zhi-Hua Zhou.

Distinguished Contributions: Professor Zhou’s distinctive research contributions in Machine Learning and Data Mining areas can be witnessed, e.g., by his many papers published in premium journals/conferences such as the AIJ (8), IEEE PAMI (6), IEEE TKDE (9), AAAI (30), IJCAI (18), ICML (9), NIPS (4), COLT (2) and KDD (6). According to GoogleScholar, his publications have received 20,000+ citations, with H-index 71, and 19 papers are with 200+ citations.

His research has been highly motivated by the core challenge of predictive modeling, i.e., generalization. Aiming to improve generalization ability of learning systems, Zhi-Hua spans his research in two wings: On one wing, he tries to construct stronger models, and thus he emphasizes studies on ensemble methods; on the other wing, he tries to study data encountered in real situations, and thus he focuses on learning from multi-labeled and partially-labeled data. First, Zhi-Hua is one of the leaders in the research of “ensemble learning” in the world. Because ensemble methods are usually with superior learning performance, they have been widely adopted by almost all winners of various data analysis competitions such as Kaggle competitions and KDDCups. Zhi-Hua’s work helped refine the scope of this area. For example, his AIJ 2002 paper received 1,280+ citations, this impressive citation number clearly shows the high impact of this work. His book “Ensemble Methods: Foundations and Algorithms” has been well-recognized as “bible in ensemble methods”. Second, Zhi-Hua is a leading expert in the research of learning from multi-labeled and partially-labeled data; involving multi-label learning, multi-instance learning, semi-supervised learning. For example, his MLkNN algorithm has become a common standard and one of the most often used multi-label learning algorithm; it has been implemented in the online MULAN toolbox by an European group, and applied by many researchers to various tasks such as image annotation, text categorization, gene function selection, etc. The corresponding paper received 900+ citations. In addition to theoretical and algorithmic contributions, he has also made significant contributions to practical applications. He held 14 patents, and developed many application systems.

Service Contributions: Zhi-Hua has distinctive contributions to the community by his outstanding services. He served on editorial boards for more than twenty journals, and served as chairs or program committee members for all major conferences in his research fields. He has served as General Chair of IEEE ICDM 2016, Program Chair of IEEE ICDM 2015, SIAM Data Mining Conference 2013, IJCAI’ 2015 Machine Learning Track, among many other conferences. He is also the founder of the ACML conference series.

PAKDD Contributions: Zhi-Hua has made great contributions to PAKDD. He served as Steering Committee member from 2007, and life member from 2015. He served as General Chair for PAKDD 2014, Program Chair for PAKDD 2007 and 2015, Area Chair/SPC, PC member for many times. He has served as Keynote speaker for PAKDD 2011. His paper won the PAKDD 2008 Best Paper Award, and he was the team leader for PAKDD 2006 Data Mining Competition (Open Category) Grand Champion, and PAKDD 2012 Data Mining Competition (Open Category) Grand Prize Winner. Education contributions: Zhi-Hua is also a talented educator. He has supervised eleven PhD students in completion, among which eight students have won the “CCF Distinguished PhD Thesis Award”, which is a prestigious award presented by the China Computer Federation, each year only 10 PhD theses in computer science in the whole country will be selected. That means, his students achieved 10% of all awards for the whole country! Many of his students have become active data mining researchers in both academia and industry.

Zhi-Hua is an AAAI Fellow, IEEE Fellow, IAPR Fellow, IET/IEE Fellow, CCF Fellow and ACM Distinguished Scientist.