Advanced Data Mining and Applications

1. Front Matter

   PDF

2. Keynotes

   1. Confucius and “Its” Intelligent Disciples

      • Edward Y. Chang

      Pages 1-1

   2. From Machine Learning to Child Learning

      • Charles Ling

      Pages 2-2

   3. Sensitivity Based Generalization Error for Supervised Learning Problems with Application in Feature Selection

      • Daniel S. Yeung

      Pages 3-3

   4. Data Mining in Financial Markets

      • Longbing Cao

      Pages 4-4

3. Regular Papers

   1. Cluster Analysis Based on the Central Tendency Deviation Principle

      • Julien Ah-Pine

      Pages 5-18

   2. A Parallel Hierarchical Agglomerative Clustering Technique for Billingual Corpora Based on Reduced Terms with Automatic Weight Optimization

      • Rayner Alfred

      Pages 19-30

   3. Automatically Identifying Tag Types

      • Kerstin Bischoff, Claudiu S. Firan, Cristina Kadar, Wolfgang Nejdl, Raluca Paiu

      Pages 31-42

   4. Social Knowledge-Driven Music Hit Prediction

      • Kerstin Bischoff, Claudiu S. Firan, Mihai Georgescu, Wolfgang Nejdl, Raluca Paiu

      Pages 43-54

   5. Closed Non Derivable Data Cubes Based on Non Derivable Minimal Generators

      • Hanen Brahmi, Tarek Hamrouni, Riadh Ben Messaoud, Sadok Ben Yahia

      Pages 55-66

   6. Indexing the Function: An Efficient Algorithm for Multi-dimensional Search with Expensive Distance Functions

      • Hanxiong Chen, Jianquan Liu, Kazutaka Furuse, Jeffrey Xu Yu, Nobuo Ohbo

      Pages 67-78

   7. Anti-germ Performance Prediction for Detergents Based on Elman Network on Small Data Sets

      • Anqi Cui, Hua Xu, Peifa Jia

      Pages 79-90

   8. A Neighborhood Search Method for Link-Based Tag Clustering

      • Jianwei Cui, Pei Li, Hongyan Liu, Jun He, Xiaoyong Du

      Pages 91-103

   9. Mining the Structure and Evolution of the Airport Network of China over the Past Twenty Years

      • Zhengbin Dong, Wenjie Wu, Xiujun Ma, Kunqing Xie, Fengjun Jin

      Pages 104-115

   10. Mining Class Contrast Functions by Gene Expression Programming

       • Lei Duan, Changjie Tang, Liang Tang, Tianqing Zhang, Jie Zuo

       Pages 116-127

   11. McSOM: Minimal Coloring of Self-Organizing Map

       • Haytham Elghazel, Khalid Benabdeslem, Hamamache Kheddouci

       Pages 128-139

   12. Chinese Blog Clustering by Hidden Sentiment Factors

       • Shi Feng, Daling Wang, Ge Yu, Chao Yang, Nan Yang

       Pages 140-151

   13. Semi Supervised Image Spam Hunter: A Regularized Discriminant EM Approach

       • Yan Gao, Ming Yang, Alok Choudhary

       Pages 152-164

   14. Collaborative Filtering Recommendation Algorithm Using Dynamic Similar Neighbor Probability

       • Chuangguang Huang, Jian Yin, Jing Wang, Lirong Zheng

       Pages 165-174

   15. Calculating Similarity Efficiently in a Small World

       • Xu Jia, Yuanzhe Cai, Hongyan Liu, Jun He, Xiaoyong Du

       Pages 175-187

This volume contains the proceedings of the International Conference on Advanced Data Mining and Applications (ADMA 2009), held in Beijing, China, during August 17–19, 2009. We are pleased to have a very strong program. Acceptance into the conference proceedings was extremely competitive. From the 322 submissions from 27 countries and regions, the Program Committee selected 34 full papers and 47 short papers for presentation at the conference and inclusion in the proceedings. The c- tributed papers cover a wide range of data mining topics and a diverse spectrum of interesting applications. The Program Committee worked very hard to select these papers through a rigorous review process and extensive discussion, and finally c- posed a diverse and exciting program for ADMA 2009. An important feature of the main program was the truly outstanding keynote spe- ers program. Edward Y. Chang, Director of Research, Google China, gave a talk titled "Confucius and 'Its' Intelligent Disciples". Being right in the forefront of data mining applications to the world's largest knowledge and data base, the Web, Dr. Chang - scribed how Google's Knowledge Search product help to improve the scalability of machine learning for Web-scale applications. Charles X. Ling, a seasoned researcher in data mining from the University of Western Ontario, Canada, talked about his in- vative applications of data mining and artificial intelligence to gifted child education.

• Clustering
• classification
• cluster analysis
• collaborative filtering
• crawling
• data mining
• ensemble classification
• knowledge discovery
• machine learning
• multi-dimensional search
• self-organizing
• self-organizing map
• visualization
• web mining

• Knowledge Science & Engineering Institute, School of Education Technology, Beijing Normal University, Beijing, China

  Ronghuai Huang

• The Hong Kong University of Science and Technology, Clear Water Bay,, Hong Kong, Hong Kong

  Qiang Yang

• School of Computing Science, Simon Fraser University, Burnaby, Canada

  Jian Pei

• Faculty of Economics, University of Porto, Porto, Portugal

  João Gama

• School of Information, Zhongguancum, Renmin University, Beijing, China

  Xiaofeng Meng

• School of Information Technology and Electrical Engineering, The University of Queensland, St. Lucia, Australia

  Xue Li

Policies and ethics