AI 2008: Advances in Artificial Intelligence

1. Grammar and Language Processing

   1. Learning to Find Relevant Biological Articles without Negative Training Examples

      • Keith Noto, Milton H. Saier Jr., Charles Elkan

      Pages 202-213

   2. Humor Prevails! - Implementing a Joke Generator into a Conversational System

      • Pawel Dybala, Michal Ptaszynski, Shinsuke Higuchi, Rafal Rzepka, Kenji Araki

      Pages 214-225

2. Statistical Learning

   1. Improving Transductive Support Vector Machine by Ensembling

      • Tao Li, Yang Zhang

      Pages 226-235

   2. Kernels Based on Distributions of Agreement Subtrees

      • Kilho Shin, Tetsuji Kuboyama

      Pages 236-246

   3. Practical Bias Variance Decomposition

      • Remco R. Bouckaert

      Pages 247-257

   4. Using Gaussian Processes to Optimize Expensive Functions

      • Marcus Frean, Phillip Boyle

      Pages 258-267

   5. Discriminant Analysis Methods for Microarray Data Classification

      • Chuanliang Chen, Yun-Chao Gong, Rongfang Bie

      Pages 268-277

   6. Propositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis

      • Stefan Mutter, Bernhard Pfahringer, Geoffrey Holmes

      Pages 278-288

3. Machine Learning

   1. Improving Promoter Prediction Using Multiple Instance Learning

      • P. J. Uren, R. M. Cameron-Jones, A. H. J. Sale

      Pages 289-299

   2. Revisiting Multiple-Instance Learning Via Embedded Instance Selection

      • James Foulds, Eibe Frank

      Pages 300-310

   3. Decision Tree Induction from Numeric Data Stream

      • Satoru Nishimura, Masahiro Terabe, Kazuo Hashimoto

      Pages 311-317

   4. L1 LASSO Modeling and Its Bayesian Inference

      • Junbin Gao, Michael Antolovich, Paul W. Kwan

      Pages 318-324

   5. Discriminating Against New Classes: One-class versus Multi-class Classification

      • Kathryn Hempstalk, Eibe Frank

      Pages 325-336

   6. Building a Decision Cluster Classification Model for High Dimensional Data by a Variable Weighting k-Means Method

      • Yan Li, Edward Hung, Korris Chung, Joshua Huang

      Pages 337-347

   7. Locality Spectral Clustering

      • Yun-Chao Gong, Chuanliang Chen

      Pages 348-354

   8. Mining Arbitrarily Large Datasets Using Heuristic k-Nearest Neighbour Search

      • Xing Wu, Geoffrey Holmes, Bernhard Pfahringer

      Pages 355-361

   9. Cross-Domain Knowledge Transfer Using Semi-supervised Classification

      • Yi Zhen, Chunping Li

      Pages 362-371

   10. On the Limitations of Scalarisation for Multi-objective Reinforcement Learning of Pareto Fronts

       • Peter Vamplew, John Yearwood, Richard Dazeley, Adam Berry

       Pages 372-378

   11. An Approach for Generalising Symbolic Knowledge

       • Richard Dazeley, Byeong-Ho Kang

       Pages 379-385

   12. Single-Cycle Image Recognition Using an Adaptive Granularity Associative Memory Network

       • Anang Hudaya Muhamad Amin, Asad I. Khan

       Pages 386-392

This book constitutes the refereed proceedings of the 21th Australasian Joint Conference on Artificial Intelligence, AI 2008, held in Auckland, New Zealand, in December 2008. The 42 revised full papers and 21 revised short papers presented together with 1 invited lecture were carefully reviewed and selected from 143 submissions. The papers are organized in topical sections on knowledge representation, constraints, planning, grammar and language processing, statistical learning, machine learning, data mining, knowledge discovery, soft computing, vision and image processing, and AI applications.

• Constraint
• artificial intelligence
• data mining
• image processing
• intelligence
• knowledge
• knowledge discovery
• knowledge representation
• learning
• machine learning

• Wales, School of Computer Science and Engineering,, University of New South, Sydney, Australia

  Wayne Wobcke

• School of Mathematics, Statistics and Computer Science, Victoria University of Wellington, Wellington, New Zealand

  Mengjie Zhang

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