Introduction to PRICAI-08


Welcome to PRICAI-08

The Pacific Rim International Conference on Artificial Intelligence (PRICAI) is a biennial international event which concentrates on AI theories, technologies and their applications in the areas of social and economic importance for countries in the Pacific Rim. In the past conferences have been held in Nagoya (1990), Seoul (1992), Beijing (1994), Cairns (1996), Singapore (1998), Melbourne (2000), Tokyo (2002), Auckland (2004) and Quilin (2006).

The Program Committee invites technical papers on substantial, original, and unpublished research in all aspects of Artificial Intelligence (AI). PRICAI-08 aims to bring together a large and diverse community, which includes practitioners, researchers, educators, and users. The conference URL is http://www.jaist.ac.jp/PRICAI-08.

The conference poster in PDF format can be downloaded here.

There are two AI-related conferences organized in connection with PRICAI'08 in Hanoi:

PRICAI'08 and each of these connected conferences will have discount of registration free for participants who attend two conferences. We will also have social activities on December 20-21 in between PRICAI'08 and KICSS'08.

Conference Organizers

Conference Chairs
Hiroshi Motoda, AOARD/Osaka University, Japan
Email:
motoda@ar.sanken.osaka-u.ac.jp
Bach Hung Khang, Vietnamese Academy of Science and Technology, Vietnam
Email:
bhkhang@ioit.ac.vn

Program Committee Chairs
Ho Tu Bao, Japan Advanced Institute of Science and Technology, Japan
Email:
bao@jaist.ac.jp
Zhi-Hua Zhou , Nanjing University, China
Email:
zhouzh@nju.edu.cn

Organizing Chairs
Tu Bao Ho, Japan Advanced Institute of Science and Technology, Japan
Email:
bao@jaist.ac.jp
Nguyen Ngoc Binh, College of Technology, VNU-HN, Vietnam
Email:
nnbinh@vnu.edu.vn
Pham Hoang Luong, Hanoi University of Technology, Vietnam
Email:
hoang-luongpham@mail.hut.edu.vn
Luong Chi Mai
, Institute of Information Technology, VAST, Vietnam
Email:
lcmai@ioit.ac.vn

Workshop Chairs
Duc Nghia Pham, NICTA/Griffth, Australia
Email:
duc-nghia.pham@nicta.com.au
Takashi Washio,
Osaka University, Japan
Email:
washio@ar.sanken.osaka-u.ac.jp

Tutorial Chair
Aditya K. Ghose, University of Wollongong, Australia
Email:
aditya@uow.edu.au
Tru Hoang Cao, Ho Chi Minh City University of Technology
Email:
tru@cse.hcmut.edu.vn

Publication Chair
Saori Kawasaki, Japan Advanced Institute of Science and Technology, Japan
Email:
skawasa@jaist.ac.jp

Registration Chairs
Ngo Cao Son, Vietnamese Academy of Science and Technology, Vietnam
Email:
ncson@ioit.ac.vn
Saori Kawasaki, Japan Advanced Institute of Science and Technology, Japan
Email:
skawasa@jaist.ac.jp

Industrial Chair
Minh B. Do, Palo Alto Research Center, USA
Email:
Minh.Do@parc.com

Web Master
Motoki Miura, Japan Advanced Institute of Science and Technology
Email: miuramo@jaist.ac.jp
Dang Hung Tran,
Japan Advanced Institute of Science and Technology
Email: hungtd@jaist.ac.jp

Ngoc Khanh Pham,
Japan Advanced Institute of Science and Technology
Email: khanh@jaist.ac.jp


Steering Committee

Wai K. Yeap (Chair)
Abdul Sattar (Secretary-Treasurer)
Tru Hoang Cao
Randy Goebel
Mitsuri Ishizuka
Fangzhen Lin
Hiroshi Motoda
Hideyuki Nakashima
Nancy Reed
R. Sadananda
Mohd. Sapiyan
Geoff Webb
Chengqi Zhang





Program Committee
 

Chairs

 

Tu Bao Ho  Japan Advanced Institute of Science and Technology
Zhi-Hua Zhou Nanjing University 

 

Vice-Chairs

 

Naoki Abe IBM T.J. Watson Research Center
Hung H. Bui SRI International
Peter Flach University of Bristol
Eibe Frank University of Waikato
Randy Goebel University of Alberta
Achim Hoffmann University of New South Wales
James Kwok Hong Kong University of Science and Technology
Doheon Lee Korean Advanced Institute of Science and Technology
Riichiro Mizoguchi Osaka University
Wee Keong Ng Nanyang Technological University
Satoshi Tojo  Japan Advanced Institute of Science and Technology
Abdul Sattar Griffith University
Qiang Yang Hong Kong University of Science and Technology
Chengqi Zhang University of Technology, Sydney
Limsoon Wong National University of Singapore

 

Members

 

David Albrecht Monash University
Rajenda Akerkar Technomathematics Research Foundation
Aijun An  York University
Mike Barley  University of Auckland
Laxmidhar Behera  Indian Institute of Technology, Kanpur
Hendrik Blockeel  Katholieke Universiteit Leuven
Jean-François Boulicaut  Institut National des Sciences Appliquées de Lyon
Longbing Cao  University of Technology, Sydney
Tru Hoang Cao  Ho Chi Minh City University of Technology
Nicholas Cercone  Dalhousie University
Sanjay Chawla  University of Sydney
Phoebe Y-P Chen  Deakin University
Songcan Chen  Nanjing University of Aeronautics and Astronautics 
Zheng Chen  Microsoft Research Asia
Jian-Hung Chen  Chung Hua University
Shu-Ching Chen  Florida International University
David W-L Cheung  The University of Hong Kong
Yiu-ming Cheung  Hong Kong Baptist University
Sung-Bae Cho  Yonsei University
Paul Compton  University of New South Wales
Jirapun Daengdej  Assumption University
Raedt Luc De  Katholieke Universiteit Leuven
Minh B. Do  Palo Alto Research Center
AnHai Doan  University of Wisconsin-Madison
Anh Duc Duong  Ho Chi Minh City University of Natural Sciences
Fazel Famili  National Research Council
Wei Fan  IBM T.J. Watson Research Center
Hamido Fujita Iwate Prefectural University
Peter A. Flach  University of Bristol
Joao Gama  University of Porto
Dragan Gamberger  Rudjer Boskovic Institute
Yang Gao 
Nanjing University
Sharon XiaoYing Gao  Victoria University of Wellington
Fosca Giannotti ISTI, CNR di Pisa
Xin Geng  Deakin University
Peter Haddawy  Asian Institute of Technology
James Harland  RMIT University
Kazuo Hashimoto Tohoku University
Takashi Hashimoto  Japan Advanced Institute of Science and Technology
Koichi Hori  University of Tokyo
Wynne Hsu  National University of Singapore
Xiangji Huang  York University
Joshua Huang  The University of Hong Kong
Shell Ying Huang  Nanyang Technological University
Van Nam Huynh  Japan Advanced Institute of Science and Technology
Mitsuru Ikeda  Japan Advanced Institute of Science and Technology
Rolly Intan Petra Christian University, Indonesia
Sanjay Jain  National University of Singapore
Zhi Jin  CAS
Geun Sik Jo  Inha University
Jeffey Junfeng Google Inc.
Ken Kaneiwa  National Institute of Informatics
Byeong Ho Kang  University of Tasmania
Hiroyuki Kawano  Kyoto University 
Masatsugu Kidode  Nara Institute of Science and Technology
Boonserm Kijsirikul  Chulalongkorn University
Eun Yi Kim  Konkuk University
Masahiro Kimura  Ryukoku University
Yasuhiko Kitamura  Kwansei Gakuin University
Peep Küngas  SOA Trader, Ltd.
Susumu Kunifuji  Japan Advanced Institute of Science and Technology
Satoshi Kurihara  Osaka University
Wai Lam  Chinese University of Hong Kong
Nada Lavrac  Jozef Stefan Insititute
Wee Sun Lee  National University of Singapore
Tze Yun Leong  National University of Singapore
Xue Li  The University of Queensland
Chun-Hung Li  Hong Kong Baptist University
Zhoujun Li  Beihang University
Gerard Ligozat  University Paris-Sud
Ee-Peng Lim  Nanyang Technological University
Jiming Liu  Hong Kong Baptist University
Huan Liu  Arizona State University
Yi Liu Google Inc.
Xudong Luo University of Southampton
Chi Mai Luong Vietnam Academy of Science and Technology
Jixin Ma  University of Greenwich
Michael J. Maher  University of New South Wales
Donato Malerba  University of Bari
Yuji Matsumoto  Nara Institute of Science and Technology
Gordon McCalla  University of Saskatchewan
Chris Messon  Massey University
Antonija Mitrovic  University of Canterbury
Yohei Murakami National Institute of Information and Communications Technology
Shivashankar B. Nair  Indian Institute of Technology Guwahati
Le Minh Nguyen Japan Advanced Institute of Science and Technology
Hung Son Nguyen  University of Warsaw
Ngoc Binh Nguyen  College of Technology
Thanh Thuy Nguyen  Hanoi University of Technology
Trong Dung Nguyen Vietnam Academy of Science and Technology
Takashi Okada  Kwansei Gakuin University
Manabu Okumura  Tokyo Institute of Technology
Jeffrey Junfeng Pan Google Inc.
Jeng-Shyang Pan 
National Kaohsiung University
Hyeyoung Park  Kyungpook National University
Seong-Bae Park  Kyungpook National University
Jose M Pena  Universidad Politécnica de Madrid
Xuan Hieu Phan Tohoku University
Tho Hoan Pham  Hanoi National University of Education
Fred Popowich  Simon Fraser University
Arun K. Pujari  University of Hyderabad
Hiok Chai Quek  Nanyang Technological University
Joel Quinqueton  University Monpellier 3
Anca Luminita Ralescu  University of Cinicnnati
Debbie Richard  Macquarie University
Pat Riddle  University of Auckland
Fabio Roli  University of Cagliari
Kazumi Saito  University of Shizuoka
Kenji Satou  Kanazawa University
Rudy Setiono  National University of Singapore
Yidong Shen  CAS
Daming Shi  Nanyang Technological University
Akira Shimazu  Japan Advanced Institute of Science and Technology
Kiyoaki Shirai  Japan Advanced Institute of Science and Technology
Arul Siromoney  Anna University
Kate Smith-Miles  Deakin University
Von-Wun Soo  National Tsing-Hua University
Eiichiro Sumita  Advanced Telecommunications Research Institute International
Ho Ha Sung Kyungpook National University
Wing Kin Sung  National University of Singapore
Hideaki Takeda  National Institute of Informatics
An Hwee Tan  Nanyang Technological University
Chew Lim Tan  National University of Singapore
David Taniar  Monash University
Takao Terano  Tokyo Institute of Technology
Alexandre Termier  Université Joseph Fourier
Thanaruk Theeramunkong  Thammasat University
John Thornton  Griffith University
Kai Ming Ting  Monash University
Cao Son Tran  New Mexico State University
Shusaku Tsumoto  Shimane University
Toby Walsh  University of New South Wales
Lipo Wang  Nanyang Technological University
Hui Wang  University of Ulster
Takashi Washio  Osaka University
Ian Watson  University of Auckland
Graham Williams  Australian National University
Wayne Wobcke  University of New South Wales
Mingrui Wu  Max Planck Institute for Biological Cybernetics
Xintao Wu  University of North Carolina at Charlotte
Hui Xiong  Rutgers University
Xiangyang Xue  Fudan University
Seiji Yamada  National Institute of Informatics
Ying Yang  Monash University
Hyun Seung Yang  KAIST 
Yiyu Yao  University of Regina
Roland H.C Yap  National University of Singapore
Jieping Ye  jieping.ye@asu.edu
Dit-Yan Yeung  Hong Kong University of Science and Technology
Jeffrey Xu Yu  Chinese University of Hong Kong
Kai Yu  NEC Labs America
Lei Yu  Binghamton University
Philip Yu  University of Illinois at Chicago
Shipeng Yu  Siemens Medical Solutions USA
Pong Chi Yuen  Hong Kong Baptist University
Yifeng Zeng Aalborg University Denmark
Hongbin Zha  Peking University
Dongmo Zhang  University of Western Sydney
Shichao Zhang  University of Technology, Sydney
Zili Zhang  Deakin University
Benyu Zhang  Microsoft Research Asia
Bo Zhang  Tsinghua University
Changshui Zhang  Tsinghua University
Daoqiang Zhang  Nanjing University of Aeronautics and Astronautics 
Junping Zhang  Fudan University
Liqing Zhang  Shanghai Jiaotong University
Min-Ling Zhang  Hohai University
Byoung-Tak Zhang  Seoul National University
Du Zhang  California State University at Sacramento
Jian Zhang  Carnegie Mellon University
Weixiong Zhang  Washington University in St. Louis
Yanqing Zhang  Georgia State University
Zhongfei (Mark) Zhang  Binghamton University
Alice Zheng  Carnegie Mellon University
Ning Zhong  Maebashi Institute of Technology
Aoying Zhou  Fudan University
Shuigeng Zhou  Fudan University
Yan Zhou  University of South Alabama
Jerry Zhu  University of Wisconsin-Madison
Xinquan Zhu  Florida Atlantic University
Jean-Daniel Zucker  LIP6 Paris


 

 


Keynote and Invited Speakers

Keynote speaker:

 

Paul Cohen
University of Arizona, USA

 


What shall we do next? The challenges of AI midway through its first century

    Abstract: After half a century of productive work, let us pause to consider what to do next. Looking back we see that Turing's Test was a destination without a map, a goal without a methodology.  We see three major, gradual retreats from AI's original goals --- general intelligence, knowledge-based intelligence, and problem solving. We see the fragmentation of AI into sub-disciplines and growing uncertainty about who we are and what we want to accomplish.  Yet I am optimistic:  With an informed understanding of our past we can design and run large-scale, goal-directed research programs -- as other organized sciences do -- and if we do so with vision and discipline we may yet see Turing's Test passed -- and our understanding of intelligence dramatically increased -- before the end of our first century. This is already happening in several areas of AI, as I will illustrate in my talk.
   
Biographical Sketch
:  Paul Cohen is Professor and Head of Computer Science at the University of Arizona.  Following graduate work in Computer Science and Psychology at Stanford University, Cohen became a professor in the Department of Computer Science at the University of Massachusetts, Amherst in 1983.  From 2003-2008  he was Director of the Center for Research on Unexpected Events at USC's Information Sciences Institute. Cohen's research is in the areas of planning, learning, data mining, various aspects of cognitive science, and the history and methodology of Artificial Intelligence. 
 

 

Invited speakers:
 

 

Hendrik Blockeel
K.U.Leuven , Belgium, and Leiden University, The Netherlands

 

 

 


Exposing the causal structure of processes by learning CP-logic programs

    Abstract: Since the late nineties there has been an increased interested in probabilistic logic learning, an area within AI that combines machine learning with logic-based knowledge representation and uncertainty reasoning.  Several different formalisms for combining first-order logic with probability reasoning have been proposed, and it has been studied how models in these formalisms can be automatically learned from data.

This talk starts with a brief introduction to probabilistic logic learning, after which we will focus on a relatively new formalism known as CP-logic. CP-logic stands for "causal probabilistic logic". It is a knowledge representation formalism that allows us to write down rules that indicate that a certain combination of conditions may cause certain effects with a particular probability (e.g., tossing a coin may cause a result of heads or tails, each with 50% probability). Besides the fact that this formalism is interesting for knowledge representation in itself, it also offers interesting opportunities from the machine learning point of view.  Indeed, given the semantics of these CP-logic programs, learning them from data amounts to extracting probabilistic causal influences from data.  We will discuss recent research on learning CP-logic programs, including: algorithms for learning them; how they relate to graphical models; and applications of learning CP-logic programs.

   
Bioraphy
: Hendrik Blockeel holds Masters degrees in Computer Science (1993) and Artificial Intelligence (1994), and a PhD in Computer Science (1998) from the Katholieke Universiteit Leuven, Belgium.  He is a post-doctoral fellow of the Research Foundation - Flanders (1999-2008), and holds associate professor positions at the Department of Computer Science of the Katholieke Universiteit Leuven and at the Leiden Institute of Advanced Computer Science (Leiden, The Netherlands).  His main research interests are in data mining and machine learning, with a focus on learning from relational, logical or graph representations, and on the integration of probabilistic information and inference into this.  He published over 100 peer-reviewed papers on these subjects.  He was program chair of the European Conference on Machine Learning in 2003 and of the International Conference on Inductive Logic Programming in 2007. He is an editorial board member of several journals, including Machine Learning, and is a board member of the European Coordinating Committee for Artificial Intelligence.
 

 

   
  An-Hai Doan
University Wisconsin Madison, USA

 


 

Building Structured Web Community Portals via Extraction, Integration, and Mass Collaboration

   

Abstract: The World-Wide Web hosts numerous communities, each focusing on a particular topic. As such communities proliferate, so do efforts to build community portals. Most current portals are organized according to topic taxonomies. Recently, however, there has been a growing effort to build structured data portals (e.g., IMDB, Citeseer) that present a unified view of entities and relationships in the community. Such portals can prove extremely valuable in a wide range of domains. But how can we build them efficiently?

In this talk, I will present a new research vision that addresses this question. The goal is to develop a system that a small team (or ideally just one person) can quickly deploy to build an initial (but already useful) structured portal, then leverage the entire community in a mass collaboration fashion to improve and expand this portal. As such, the research agenda requires combining and extending research in information extraction, information integration, and Web 2.0 technologies, among others. This agenda is actively being pursued in the Cimple project, a joint effort between the University of Wisconsin and Yahoo Research. In the talk I will describe recent progress in Cimple, portal prototypes, lessons learned, and future directions. I will focus in particular on how Cimple raises interesting and novel challenges for both AI and database research. More information about Cimple can be found at www.cs.wisc.edu/~anhai/projects/cimple.

   
Biography
: AnHai Doan is an associate professor in Computer Science at the University of Wisconsin-Madison. His interests cover databases, AI, and Web. His current research focuses on data integration, Web community management, mass collaboration, text management, information extraction, and schema and ontology matching. Selected recent honors include the ACM Doctoral Dissertation Award in 2003, CAREER Award in 2004, and Alfred P. Sloan Research Fellowship in 2007. Selected recent professional activities include co-chairing WebDB at SIGMOD-05 and the AI Nectar track at AAAI-06.
 

 

   

 

  Yuji Matsumoto
Nara Institute of Science and Technology, Japan

 

 


Large Scale Corpus Analysis and Recent Applications

   

Abstract: Recent progress of corpus and machine learning-based natural language processing methodologies have made it possible to handle large scale corpus with a quite high accuracy.  The speaker is now involved in a project for constructing a large scale contemporary Japanese balanced corpus, aiming at constructing automatic annotation tools on various levels of natural language analyses.  I will first introduce our activities on corpus based natural language analyzers for word dependency parsing and anaphora resolution and annotated corpus management environment.  Then, I will explain recent natural language applications such as sentiment/opinion mining and knowledge extraction from a large scale text data like Weblogs.

   


Biography: Yuji Matsumoto received Master and PhD degrees in Information Science from Kyoto University.  He is currently a professor at the Graduate School of Information Sicence in Nara Institute of Science and Technology.  He and his group have developed lots of machine learning-based natural language processing tools such as ChaSen and CaboCha as well as Japanese and Chinese dictionaries, all of which are publicly available.  His research interests cover corpus-based natural language processing, knowledge acquisition, lexical semantics, text mining and integration of empirical and theoretical natural language techniques.

 


Sponsors of PRICAI-08

FPT Company

 

 
 Asian Office of Aerospace Research and Development AFOSR/AOARD

 

 

Vietnamese Academy of Science and Technology (VAST)

Institue of Information Technology (IOIT), Vietnamese Academy of Science and Technology (VAST)

Hanoi University of Technology (HUT)

College of Technology,
Vietnam National University, Hanoi
     
   
   

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