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Communications and Discoveries from Multidisciplinary Data

  • Book
  • © 2008

Overview

Editors:
  1. Shuichi Iwata

    1. Graduate School of Engineering, The University of Tokyo, Tokyo, Japan

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  2. Yukio Ohsawa

    1. Department of Systems Innovation School of Engineering, The University of Tokyo, Tokyo, Japan

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  3. Shusaku Tsumoto

    1. Department of Medical Informatics School of Medicine, Shimane University, Enya-cho Izumo City Shimane, Japan

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  4. Ning Zhong

    1. Department of Information Engineering, Maebashi Institute of Technology, Maebashi-City, Japan
      WICI/BJUT, China

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  5. Yong Shi

    1. Research Center on Data Technology and Knowledge Economy, Chinese Academy of Sciences, Beijing, PR China
      College of Information Science and Technology, University of Nebraska, Omaha, USA

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  6. Lorenzo Magnani

    1. Department of Philosophy, University of Pavia, Pavia, Italy

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  • Selected Papers on Data based Discovery and Communication, from CODATA06
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 123)

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About this book

A number of urgent problems are rising to human life: The attack of terrorists is hard to predict, due to the hidden leaderships. New diseases are hard to extinguish, due to their new causes. Products may be shortly abandoned, due to the appearance of new desires.
A common feature of recent socially high-impact problems, such as detecting the causal virus of SARS, is that they are open to multiple scientific domains. In order to respond to this social requirement, this book collects selected papers by authors for CODATA 2006, which are relevant to the discoveries of knowledge, risk, and opportunities by combining data from multiple disciplines.
By presenting papers in this book, we aim at urging the development of data-based methods and methodologies for interdisciplinary and creative communications for solving emerging social problems. The reader shall view the direction to combine three methodological frameworks: data mining, data sharing, and communication in the contexts of sciences and businesses.

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Keywords

Table of contents (20 chapters)

  1. Front Matter

    Pages I-XIII
    Download chapter PDF

  3. Creative Community Working on Multidisciplinary Data

    1. Augmented Analytical Exploitation of a Scientific Forum

      • Xijin Tang, Yijun Liu, Wen Zhang
      Pages 65-79

    2. Multi-Data Mining for Understanding Leadership Behavior

      • Naohiro Matsumura, Yoshihiro Sasaki
      Pages 81-94

    3. Discussion Visualization on a Bulletin Board System

      • Wataru Sunayama
      Pages 95-109

    4. Design of BBS with Visual Representation for Online Data Analysis

      • Yasufumi Takama, Yuta Seo
      Pages 111-126

    5. A Study on Web Clustering with Respect to XiangShan Science Conference

      • Wen Zhang, Xijin Tang
      Pages 127-136

  4. Discoveries from Data and Application to Business

    1. A Multilevel Integration Approach for E-Finance Portal Development

      • Jia Hu, Ning Zhong
      Pages 139-155

    2. Integrated Design Framework for Embedded GUI System

      • Noriyuki Kushiro, Yukio Ohsawa
      Pages 157-170

    3. A Unified Probabilistic Inference Model for Targeted Marketing

      • Jiajin Huang, Ning Zhong
      Pages 171-186

    4. Computational Methods for Discoveries from Integrated Data - Human-Interactive Annealing for Multilateral Observation

      • Yoshiharu Maeno, Kenichi Horie, Yukio Ohsawa
      Pages 187-203

    5. Human-Interactive Annealing Process with Pictogram for Extracting New Scenarios for Patent Technology

      • Kenichi Horie, Yoshiharu Maeno, Yukio Ohsawa
      Pages 205-219

    6. Pharmaceutical Drug Design Using Dynamic Connectionist Ensemble Networks

      • Ajith Abraham, Crina Grosan, Stefan Tigan
      Pages 221-231

    7. A Framework of Knowledge Management Platform for Middle and Small Business

      • Xingsen Li, Jun Li, Yuejin Zhang, Yong Shi
      Pages 233-248

  5. Mining Risks from Multidisciplinary Data

    1. Discovery of Clusters from Proximity Data: An Approach Using Iterative Adjustment of Binary Classifications

      • Shoji Hirano, Shusaku Tsumoto
      Pages 251-268

    2. Evaluating Learning Algorithms to Support Human Rule Evaluation with Predicting Interestingness Based on Objective Rule Evaluation Indices

      • Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
      Pages 269-282

    3. Risk Mining for Infection Control

      • Shusaku Tsumoto, Kimiko Matsuoka, Shigeki Yokoyama
      Pages 283-297

    4. Evaluating the Error Risk of Email Filters Based on ROC Curve Analysis

      • Wenbin Li, Ning Zhong, Chunnian Liu
      Pages 299-314

    5. Categorized and Integrated Data Mining of Medical Data

      • Akinori Abe, Norihiro Hagita, Michiko Furutani, Yoshiyuki Furutani, Rumiko Matsuoka
      Pages 315-330
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Editors and Affiliations

  • Graduate School of Engineering, The University of Tokyo, Tokyo, Japan

    Shuichi Iwata

  • Department of Systems Innovation School of Engineering, The University of Tokyo, Tokyo, Japan

    Yukio Ohsawa

  • Department of Medical Informatics School of Medicine, Shimane University, Enya-cho Izumo City Shimane, Japan

    Shusaku Tsumoto

  • Department of Information Engineering, Maebashi Institute of Technology, Maebashi-City, Japan

    Ning Zhong

  • WICI/BJUT, China

    Ning Zhong

  • Research Center on Data Technology and Knowledge Economy, Chinese Academy of Sciences, Beijing, PR China

    Yong Shi

  • College of Information Science and Technology, University of Nebraska, Omaha, USA

    Yong Shi

  • Department of Philosophy, University of Pavia, Pavia, Italy

    Lorenzo Magnani

Bibliographic Information

  • Book Title: Communications and Discoveries from Multidisciplinary Data

  • Editors: Shuichi Iwata, Yukio Ohsawa, Shusaku Tsumoto, Ning Zhong, Yong Shi, Lorenzo Magnani

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-540-78733-4

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2008

  • Hardcover ISBN: 978-3-540-78732-7Published: 25 August 2008

  • Softcover ISBN: 978-3-642-09751-5Published: 18 November 2010

  • eBook ISBN: 978-3-540-78733-4Published: 17 August 2008

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XIV, 340

  • Number of Illustrations: 121 b/w illustrations

  • Topics: Mathematical and Computational Engineering, Artificial Intelligence

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