Communications and Discoveries from Multidisciplinary Data

ISBN-13: 9783642097515 / Angielski / Miękka / 2010 / 340 str.

Shuichi Iwata;Yukio Ohsawa;Shusaku Tsumoto

Opis

This book collects selected papers by authors for CODATA 2006, which are relevant to the acquisition of knowledge and the assessment of risk and opportunity that comes from combining data from a number of different disciplines.

Spis treści

Part I Thought, Communication, and Actions.- Sharing Representations and Creating Chances through Cognitive Niche Construction. The Role of Affordances and Abduction.- Discovering and Communicating through Multimodal Abduction.- Part II Creative Community working on Multidisciplinary Data.- Augmented Analytical Exploitation of a Scientific Forum.- Multi-Data Mining for Understanding Leadership Behavior.- Discussion Visualization on a Bulletin Board System.- Design of BBS with Visual Representation for Online Data Analysis.- A Study on Web Clustering with respect to XiangShan Science Conference.- Part III Discoveries from Data and Application to Business.- A Multilevel Integration Approach for E-Finance Portal Development.- Integrated Design Framework for Embedded GUI System.- A Unified Probabilistic Inference Model for Targeted Marketing.- Computational methods for discoveries from integrated data.- Human-Interactive Annealing Process with Pictogram for Extracting New Scenarios for Patent Technology.- Drug Design Using a Multi-input Multi-output Neuro-Fuzzy System.- A Framework of Knowledge Management Platform for Middle and Small Business.- Part IV Mining Risks from Multidisciplinary Data.- Discovery of Clusters from Proximity Data: An Approach Using Iterative Adjustment of Binary Classifications.- Evaluating Learning Algorithms to Support Human Rule Evaluation with Predicting Interestingness Based on Objective Rule Evaluation Indices.- Risk Mining for Infection Control.- Evaluating the Error Risk of Email Filters Based on ROC Curve Analysis.- Categorized and Integrated Data Mining of Medical Data.- Privacy-preserving Data Mining for Medical Data: Application of Data Partition Methods.

O autorze

Ning Zhong is currently head of Knowledge Information Systems Laboratory, and a professor in Department of Systems and Information Engineering, Graduate School, Maebashi Institute of Technology, Japan. He is also CEO of Web Intelligence Laboratory, Inc., a new type of venture intelligent IT business company. Before moving to Maebashi Institute of Technology, he was an associate professor in Department of Computer Science and Systems Engineering, Yamaguchi University, Japan. He is also a guest professor of Beijing University of Technology since 1998. He is the co-founder and co-chair of Web Intelligence Consortium (WIC), vice chair of the executive committee of the IEEE Computer Society Technical Committee on Computational Intelligence (TCCI), the advisory board of ACM SIGART, steering committee of IEEE International Conferences on Data Mining (ICDM), the advisory board of International Rough Set Society, steering committee of Pacific-Asia Conferences on Knowledge Discovery and Data Mining (PAKDD), coordinator and member of advisory board of a Special Interest Group on Granular Computing in Berkeley Initiative in Soft Computing (BISC/SIG-GrC).

Blurb

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.