Knowledge Acquisition: Approaches, Algorithms and Applications

1. Front Matter

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2. Machine Learning and Data Mining

   1. Experiments with Adaptive Transfer Rate in Reinforcement Learning

      • Yann Chevaleyre, Aydano Machado Pamponet, Jean-Daniel Zucker

      Pages 1-11

   2. Clustering over Evolving Data Streams Based on Online Recent-Biased Approximation

      • Wei Fan, Yusuke Koyanagi, Koichi Asakura, Toyohide Watanabe

      Pages 12-26

   3. Automatic Database Creation and Object’s Model Learning

      • Nguyen Dang Binh, Thuy Thi Nguyen

      Pages 27-39

   4. Finding the Most Interesting Association Rules by Aggregating Objective Interestingness Measures

      • Tri Thanh Nguyen Le, Hiep Xuan Huynh, Fabrice Guillet

      Pages 40-49

   5. Pruning Strategies Based on the Upper Bound of Information Gain for Discriminative Subgraph Mining

      • Kouzou Ohara, Masahiro Hara, Kiyoto Takabayashi, Hiroshi Motoda, Takashi Washio

      Pages 50-60

   6. A Novel Classification Algorithm Based on Association Rules Mining

      • Bay Vo, Bac Le

      Pages 61-75

3. Incremental Knowledge Acquisition

   1. Multiple Classification Ripple Round Rules: A Preliminary Study

      • Ivan Bindoff, Tristan Ling, Byeong Ho Kang

      Pages 76-90

   2. Generalising Symbolic Knowledge in Online Classification and Prediction

      • Richard Dazeley, Byeong-Ho Kang

      Pages 91-108

4. Web-Based Techniques and Application

   1. Using Formal Concept Analysis towards Cooperative E-Learning

      • Ghassan Beydoun

      Pages 109-117

   2. Navigation and Annotation with Formal Concept Analysis

      • Peter Eklund, Jon Ducrou

      Pages 118-121

   3. What Does an Information Diffusion Model Tell about Social Network Structure?

      • Takayasu Fushimi, Takashi Kawazoe, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda

      Pages 122-136

   4. Web Mining for Malaysia’s Political Social Networks Using Artificial Immune System

      • Ahmad Nadzri Muhammad Nasir, Ali Selamat, Md. Hafiz Selamat

      Pages 137-146

   5. Accessing Touristic Knowledge Bases through a Natural Language Interface

      • Juana María Ruiz-Martínez, Dagoberto Castellanos-Nieves, Rafael Valencia-García, Jesualdo Tomás Fernández-Breis, Francisco García-Sánchez, Pedro José Vivancos-Vicente et al.

      Pages 147-160

   6. ItemSpider: Social Networking Service That Extracts Personal Character from Individual’s Book Information

      • Tetsuya Tsukamoto, Hiroyuki Nishiyama, Hayato Ohwada

      Pages 161-172

   7. Acquiring Marketing Knowledge from Internet Bulletin Boards

      • Hiroshi Uehara, Kenichi Yoshida

      Pages 173-182

5. Domain Specific Knowledge Acquisition Methods and Applications

   1. A Design for Library Marketing System and Its Possible Applications

      • Toshiro Minami

      Pages 183-197

   2. Knowledge Audit on Special Children Communities

      • Aida Suzana Sukiam, Azizah Abdul Rahman, Wardah Zainal Abidin

      Pages 198-207

   3. A Dance Synthesis System Using Motion Capture Data

      • Kenichi Takahashi, Hiroaki Ueda

      Pages 208-217

   4. Discovering Areas of Expertise from Publication Data

      • Meredith Taylor, Debbie Richards

      Pages 218-230

This book constitutes the thoroughly refereed post-workshop proceedings of the 2008 Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, held in Hanoi, Vietnam, in December 2008 as part of 10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008. The 20 revised papers presented were carefully reviewed and selected from 57 submissions and went through two rounds of reviewing and improvement. The papers are organized in topical sections on machine learning and data mining, incremental knowledge acquisition, web-based techniques and applications, as well as domain specific knowledge acquisition methods and applications.

• artificial immune systems
• association rules
• classification
• data mining
• data semantics
• database
• database creation
• face recognition
• formal concept analysis
• general elections
• hidden context
• information retrieval
• knowledge ac
• machine learning
• reinforcement learning

• Computing Department, Division of Information and Communication Sciences, Macquarie University, Sydney, Australia

  Debbie Richards

• School of Computing ad Information Systems, University of Tasmania , Launceton, Tasmania, Australia

  Byeong-Ho Kang

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