Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

1. Information Retrieval

   1. Intelligent Information Retrieval Based on the Variable Precision Rough Set Model and Fuzzy Sets

      • Ming He, Bo-qin Feng

      Pages 184-192

   2. A Comprehensive OWA-Based Framework for Result Merging in Metasearch

      • Elizabeth D. Diaz, Arijit De, Vijay Raghavan

      Pages 193-201

   3. Efficient Pattern Matching of Multidimensional Sequences

      • Sangjun Lee, Kyoungsu Oh, Dongseop Kwon, Wonik Choi, Jiman Hong, Jongmoo Choi et al.

      Pages 202-210

   4. HQC: An Efficient Method for ROLAP with Hierarchical Dimensions

      • Xing-Ye Dong, Hou-Kuan Huang, Hong-Song Li

      Pages 211-220

   5. Knowledge Discovery Based Query Answering in Hierarchical Information Systems

      • Zbigniew W. Raś, Agnieszka Dardzińska, Osman Gürdal

      Pages 221-230

2. Image Recognition and Processing

   1. A Content-Based Image Quality Metric

      • Xinbo Gao, Tao Wang, Jie Li

      Pages 231-240

   2. A Novel Method of Image Filtering Based on Iterative Fuzzy Control

      • Rui-hua Lu, Ming Yang, Yu-hui Qiu

      Pages 241-250

   3. Land Cover Classification of IKONOS Multispectral Satellite Data: Neuro-fuzzy, Neural Network and Maximum Likelihood Methods

      • JongGyu Han, KwangHoon Chi, YeonKwang Yeon

      Pages 251-262

   4. Rough Set Approach to Sunspot Classification Problem

      • Sinh Hoa Nguyen, Trung Thanh Nguyen, Hung Son Nguyen

      Pages 263-272

   5. Jacquard Image Segmentation Method Based on Fuzzy Optimization Technology

      • Zhilin Feng, Jianwei Yin, Jiong Qiu, Xiaoming Liu, Jinxiang Dong

      Pages 273-282

3. Multimedia Applications

   1. Intelligent Algorithms for Optical Track Audio Restoration

      • Andrzej Czyzewski, Marek Dziubinski, Lukasz Litwic, Przemyslaw Maziewski

      Pages 283-293

   2. Multiresolution Pitch Analysis of Talking, Singing, and the Continuum Between

      • David Gerhard

      Pages 294-303

   3. Toward More Reliable Emotion Recognition of Vocal Sentences by Emphasizing Information of Korean Ending Boundary Tones

      • Tae-Seung Lee, Mikyoung Park, Tae-Soo Kim

      Pages 304-313

   4. Some Issues on Detecting Emotions in Music

      • Piotr Synak, Alicja Wieczorkowska

      Pages 314-322

   5. A Global-Motion Analysis Method via Rough-Set-Based Video Pre-classification

      • Zhe Yuan, Yu Wu, Guoyin Wang, Jianbo Li

      Pages 323-332

   6. Analysis and Generation of Emotionally-Charged Animated Gesticulation

      • Bożena Kostek, Piotr Szczuko

      Pages 333-341

4. Medical Applications

   1. Handling Missing Attribute Values in Preterm Birth Data Sets

      • Jerzy W. Grzymala-Busse, Linda K. Goodwin, Witold J. Grzymala-Busse, Xinqun Zheng

      Pages 342-351

   2. Attribute Selection and Rule Generation Techniques for Medical Diagnosis Systems

      • Grzegorz Ilczuk, Alicja Wakulicz-Deja

      Pages 352-361

   3. Relevant Attribute Discovery in High Dimensional Data Based on Rough Sets and Unsupervised Classification: Application to Leukemia Gene Expressions

      • Julio J. Valdés, Alan J. Barton

      Pages 362-371

   4. A Hybrid Approach to MR Imaging Segmentation Using Unsupervised Clustering and Approximate Reducts

      • Sebastian Widz, Kenneth Revett, Dominik Ślȩzak

      Pages 372-382

This volume contains the papers selected for presentation at the 10th Int- national Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2005, organized at the University of Regina, August 31st–September 3rd, 2005. This conference followed in the footsteps of inter- tional events devoted to the subject of rough sets, held so far in Canada, China, Japan,Poland,Sweden, and the USA. RSFDGrC achievedthe status of biennial international conference, starting from 2003 in Chongqing, China. The theory of rough sets, proposed by Zdzis law Pawlak in 1982, is a model of approximate reasoning. The main idea is based on indiscernibility relations that describe indistinguishability of objects. Concepts are represented by - proximations. In applications, rough set methodology focuses on approximate representation of knowledge derivable from data. It leads to signi?cant results in many areas such as ?nance, industry, multimedia, and medicine. The RSFDGrC conferences put an emphasis on connections between rough sets and fuzzy sets, granularcomputing, and knowledge discoveryand data m- ing, both at the level of theoretical foundations and real-life applications. In the case of this event, additional e?ort was made to establish a linkage towards a broader range of applications. We achieved it by including in the conference program the workshops on bioinformatics, security engineering, and embedded systems, as well as tutorials and sessions related to other application areas.

• artificial intelligence
• cognition
• data mining
• evolution
• evolutionary computation
• fuzzy
• information system
• learning
• machine learning
• multimedia
• probabilistic network
• uncertain reasoning

• Department of Computer Science, University of Regina, Regina, SK, S4S 0A2 Canada, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warsaw, P.O. Box, Poland

  Dominik Ślęzak

• Department of Computer Science, University of Regina, Regina, Canada

  JingTao Yao, Wojciech Ziarko

• Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Canada

  James F. Peters

• College of Computer and Information Engineering, Hehan University, Henan, China

  Xiaohua Hu

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