Shichao Zhang

Ray Jarvis

The 18th Australian Joint Conference on Artificial Intelligence (AI 2005) was held at the University of Technology, Sydney (UTS), Sydney, Australia from 5 to 9 December 2005. AI 2005 attracted a historical record number of submissions, a total of 535 papers. The review process was extremely selective. Out of these 535 submissions, the Program Chairs selected only 77 (14.4%) full papers and 119 (22.2%) short papers based on the review reports, making an acceptance rate of 36.6% in total. Authors of the accepted papers came from over 20 countries. This volume of the proceedings contains the abstracts of three keynote speeches and all the full and short papers. The full papers were categorized into three broad sections, namely: AI foundations and technologies, computational intelligence, and AI in specialized domains. AI 2005 also hosted several tutorials and workshops, providing an interacting mode for specialists and scholars from Australia and other countries. Ronald R. Yager, Geoff Webb and David Goldberg (in conjunction with ACAL05) were the distinguished researchers invited to give presentations. Their contributions to AI 2005 are really appreciated.

18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005, Proceedings

AI 2005: Advances in Artificial Intelligence

Chengqi Zhang

Qingfeng Chen

The present volume arose from the need for a comprehensive coverage of the state of the art in security protocol analysis. It aims to serve as an overall course-aid and to provide self-study material for researchers and students in formal methods theory and applications in e-commerce, data analysis and data mining. The volume will also be useful to anyone interested in secure e-commerce. The book is organized in eight chapters covering the main approaches and tools in formal methods for security protocol analysis. It starts with an introductory chapter presenting the fundamentals and background knowledge with respect to formal methods and security protocol analysis. Chapter 2 provides an overview of related work in this area, including basic concepts and terminology. Chapters 3 and 4 show a logical framework and a model checker for analyzing secure transaction protocols. Chapter 5 explains how to deal with uncertainty issues in secure messages, including inconsistent messages and conflicting beliefs in messages. Chapter 6 integrates data mining with security protocol analysis, and Chapter 7 develops a new technique for detecting collusion attack in security protocols. Chapter 8 gives a summary of the chapters and presents a brief discussion of some emerging issues in the field.

Models and Applications

Secure Transaction Protocol Analysis

Xindong Wu

The Web has emerged as a large, distributed data repository, and information on the Internet and in existing transaction databases can be analyzed for commercial gains in decision making. Therefore, how to efficiently identify quality knowledge from different data sources uncovers a significant challenge. This challenge has attracted wide interest from both academia and the industry. Knowledge Discovery in Multiple Databases provides a comprehensive introduction to the latest advancements in multi-database mining, and presents a local-pattern analysis framework for pattern discovery from multiple data sources. Based on this framework, data preparation techniques in multiple databases, an application-independent database classification for data reduction, and efficient algorithms for pattern discovery from multiple databases are described. Knowledge Discovery in Multiple Databases is suitable for researchers, professionals and students in data mining, distributed data analysis, and machine learning, who are interested in multi-database mining. It is also appropriate for use as a text supplement for broader courses that might involve knowledge discovery in databases and data mining.

Knowledge Discovery in Multiple Databases

This book constitutes the refereed proceedings of the 18th Australian Joint Conference on Artificial Intelligence, AI 2005, held in Sydney, Australia in December 2005. The 77 revised full papers and 119 revised short papers presented together with the abstracts of 3 keynote speeches were carefully reviewed and selected from 535 submissions. The papers are catgorized in three broad sections, namely: AI foundations and technologies, computational intelligence, and AI in specialized domains. Particular topics addressed by the papers are logic and reasoning, machine learning, game theory, robotic technology, data mining, neural networks, fuzzy theory and algorithms, evolutionary computing, Web intelligence, decision making, pattern recognition, agent technology, and AI applications.

Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.

Shichao Zhang

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