Shusaku Tsumoto – författare

Music recommendation systems are becoming more and more popular. Listening to music may improve heart rate, respiratory rate, and blood pressure in people with heart disease. The book presents a variety of approaches useful to create recommendation systems in healthcare, music, and in music therapy.

This monograph presents novel approaches and new results in fundamentals and applications related to rough sets and granular computing. It includes the application of rough sets to real world problems, such as data mining, decision support and sensor fusion. The relationship of rough sets to other important methods of data analysis - Bayes theorem, neurocomputing and pattern recognition is thoroughly examined. Another issue is the rough set based data analysis, including the study of decision making in conflict situations. Recent engineering applications of rough set theory are given, including a processor architecture organization for fast implementation of basic rough set operations and results concerning advanced image processing for unmanned aerial vehicles. New emerging areas of study and applications are presented as well as a wide spectrum of on-going research, which makes the book valuable to all interested in the field of rough set theory and granular computing.

This book constitutes the refereed proceedings of the 14th International Symposium on Methodologies for Intelligent Systems, ISMIS 2003, held in Maebashi City, Japan in October 2003.The 97 revised papers presented together with extended abstracts of 4 invited talks were carefully reviewed and selected from close to 200 submissions. The papers are organized in topical sections on knowledge discovery and data mining, knowledge representation and integration, intelligent information systems, rough sets, intelligent agent technologies, text mining, AI logic and logic programming, soft computing, intelligent information retrieval, automatic and evolutionary computation, and multimedia data processing.

This book constitutes the refereed proceedings of the 4th International Conference on Rough Sets and Current Trends in Computing, RSCTC 2004, held in Uppsala, Sweden in June 2004. The 45 revised full papers and 60 revised short papers presented together with 3 invited papers and a bibliographic project report were carefully reviewed and selected from 248 submissions. The papers are organized in topical sections on theory, logic and rough sets, granular computing, rough and fuzzy relations, foundations of data mining, incomplete information systems, interestingness, multiagents and information systems, fuzzy logic and modeling, rough classification, rough sets and probabilities, variable precision rough sets models, spatial reasoning, reduction, rule induction, rough sets and neural networks, clustering, data mining, image and signal recognition, information retrieval, decision support, adaptaive and optimization methods, bioinformatics, and medical applications.

This volume contains the papers selected for presentation at the 15th International S- posiumonMethodologiesforIntelligentSystems,ISMIS2005,heldinSaratogaSprings, NewYork,25-28May,2005. ThesymposiumwasorganizedbySUNYatAlbany. Itwas sponsored by the Army Research Of?ce and by several units of the University at Albany including its Division for Research, College of Arts and Sciences, Department of C- puter Science, and Institute for Informatics, Logics, and Security Studies (formerly the Institute for Programming and Logics). ISMIS is a conference series that was started in 1986 in Knoxville, Tennessee. Since then it has been held in Charlotte (North Carolina), Knoxville(Tennessee),Turin(Italy),Trondheim(Norway),Warsaw(Poland),Zakopane (Poland), Lyon (France), and Maebashi City (Japan). The Program Committee selected the following major areas for ISMIS 2005: intelligent information systems, knowledge discovery and data mining, knowledge - formation and integration, knowledge representation, logic for arti?cial intelligence, soft computing, Web intelligence, Web services, and papers dealing with applications of intelligent systems in complex/novel domains.The contributed papers were selected from almost 200 full draft papers by the Program Committee members: Troels Andreasen, Peter Baumgartner, Boualemn Benatallah, Salima Benbernou, Veronique Benzaken, Petr Berka, Elisa Bertino, Alan Biermann, Jacques Calmet, Sandra Carberry, Juan Carlos Cubero, Luigia Carlucci Aiello, Shu-Ching Chen, Christine Collet, Agnieszka Dardzinska, Ian Davidson, Robert Demolombe, Jitender Deogun, Jon Doyle, Tapio Elomaa, Attilio Giordana, Jerzy Grzymala-Busse,MirsadHadzikadic,ReinerHaehnle,JanuszKacprzyk,VipulKashyap, Jan Komorowski, Jacek Koronacki, Tsau Young Lin, Donato Malerba, David Maluf, Davide Martinenghi, Stan Matwin, Natasha Noy, Werner Nutt, James Peters, Jean-Marc Petit, Vijay Raghavan, Jan Rauch, Gilbert Ritschard, Erik Rosenthal, Marie-Christine Rousset, Nahid Shahmehri, Andrzej Skowron, Dominik Slezak, Nicolas Spyratos, V. S.

This volume contains the papers selected for presentation at the 2nd Inter- tional Workshop on Active Mining (AM 2003) which was organized in conju- tion with the 14th International Symposium on Methodologies for Intelligent Systems (ISMIS 2003), held in Maebashi City, Japan, 28-31 October, 2003. The workshop was organized by the Maebashi Institute of Technology in - operation with the Japanese Society for Arti?cial Intelligence. It was sponsored by the Maebashi Institute of Technology, the Maebashi Convention Bureau, the Maebashi City Government, the Gunma Prefecture Government, JSAI SIGKBS (Japanese Arti?cial Intelligence Society, Special Interest Group on Knowledge- Based Systems), a Grant-in-Aid for Scienti?c Research on Priority Areas (No. 759) "Implementation of Active Mining in the Era of Information Flood," US AFOSR/AOARD, the Web Intelligence Consortium (Japan), the Gunma Inf- mation Service Industry Association, and Ryomo Systems Co., Ltd. ISMIS is a conference series that was started in 1986 in Knoxville, Tennessee.SincethenithasbeenheldinCharlotte(NorthCarolina),Knoxville(Tennessee), Torin (Italy), Trondheim (Norway), Warsaw (Poland), Zakopane (Poland), and Lyon (France). The objective of this workshop was to gather researchers as well as prac- tioners who are working on various research ?elds of active mining, share ha- learned experiences, and shed light on the future development of active mining.

"Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state of the art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.

For this book, the editors invited and called for contributions from indispensable research areas relevant to "chance discovery," which has been defined as the discovery of events significant for making a decision, and studied since 2000.

This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007. The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.

This book constitutes the thoroughly refereed post-proceedings of the 2006 Pacific Rim Knowledge Acquisition Workshop, PKAW 2006, held in Guilin, China in August 2006 as part of 9th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006. The 21 revised full papers and 6 revised short papers presented together with 4 invited talks were carefully reviewed and selected from 81 submissions. The papers are organized in topical sections on ontology and knowledge acquisition, algorithm approaches to knowledge acquisition, incremental knowledge acquisition and RDR, knowledge acquisition and applications, as well as machine learning and data mining.

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.

The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g.

This book constitutes the proceedings of the PAKDD Workshops 2008, namely ALSIP 2008, DMDRM 2008, and IDM 2008. The workshops were held in conjunction with the PAKDD conference in Osaka, Japan, during May 20-23, 2008. The 17 papers presented were carefully reviewed and selected from 38 submissions. The International Workshop on Algorithms for Large-Sale Information Processing in Knowledge Discovery (ALSIP) focused on exchanging fresh ideas on large-scale data processing in the problems of data mining, clustering, machine learning, statistical analysis, and other computational aspects of knowledge discovery problems. The Workshop on Data Mining for Decision Making and Risk Management (DMDRM) covered data mining and machine learning approaches, statistical approaches, chance discovery, active mining and application of these techniques to medicine, marketing, security, decision support in business, social activities, human relationships, chemistry and sensor data. The Workshop on Interactive Data Mining Overview (IDM) discussed various interactive data mining researches such as interactive information retrieval, information gathering sysetms, personalization systems, recommendation systems, user interfaces.

This book constitutes the refereed proceedings of the Fourth International Conference on Rough Sets and Knowledge Technology, RSKT 2009, held in Gold Coast, Australia, in July 2009. The 85 revised full papers papers presented together with 3 keynote papers and 2 special sessions were carefully reviewed and selected from 229 submissions. The papers are organized in topical sections on rough sets and computing, rough sets and data reduction, data mining and knowledge discovery, granular computing and cognitive computing, fuzzy sets and computing, knowledge technology and intelligent systems, computational intelligence and applications, image processing and understanding, and formal concept analysis.

This monograph presents novel approaches and new results in fundamentals and applications related to rough sets and granular computing. It includes the application of rough sets to real world problems, such as data mining, decision support and sensor fusion. The relationship of rough sets to other important methods of data analysis -- Bayes theorem, neurocomputing and pattern recognition is thoroughly examined. Another issue is the rough set based data analysis, including the study of decision making in conflict situations. Recent engineering applications of rough set theory are given, including a processor architecture organization for fast implementation of basic rough set operations and results concerning advanced image processing for unmanned aerial vehicles. New emerging areas of study and applications are presented as well as a wide spectrum of on-going research, which makes the book valuable to all interested in the field of rough set theory and granular computing.

For this book, the editors invited and called for contributions from indispensable research areas relevant to "chance discovery," which has been defined as the discovery of events significant for making a decision, and studied since 2000. From respective research areas as artificial intelligence, mathematics, cognitive science, medical science, risk management, methodologies for design and communication, the invited and selected authors in this book present their particular approaches to chance discovery. The chapters here show contributions to identifying rare or hidden events and explaining their significance, predicting future trends, communications for scenario development in marketing and design, identification effects and side-effects of medicines, etc.The methods presented in this book are based on the interaction of human, machine, and human's living environment, rather than based purely automated predictions of the future. This is a promising direction of computer-supported decision of human in a radically changing environment.

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.

The aim of this book is to gather the most recent works that address issues related to the concept of mining complex data. Actually, managing complex data within the KDD process implies to work on every step, starting from the pre-processing (e.g.

Volume XII of the Transactions on Rough Sets (TRS) includes articles that are part of a special issue on Rough Set Structuring of Knowledge. These articles are extended versions of papers accepted for presentation at the Rough Set and Knowledge Technology Conference (RSKT 2008) organized in Chengdu, China, in May 2008. In fact, this conference did not take place because of the earthquake that dramatically hit the Chengdu province just before the event. The editors selected some papers accepted for RSKT 2008 and invited their authors to submit extended versions to this issue. The 11 submissions received after this invitation were sent to reviewers and, ?nally, 8 papers were accepted for publication in the special issue. The editors of the special issue are particularly grateful to all the authors of submitted papers, and to the editors of Transactions on Rough Sets,JamesF. Peters and Andrzej Skowron, who provided friendly and valuable assistance in the reviewing process.Special thanks are due to the following reviewers: Mohua Banerjee, Anna Gomolinsk ' a, Ryszard Janicki, Julia Johnson, Maneesh Joshi, Jusheng Mi, Sonajharia Minz, Sushmita Mitra, Tuan Trung Nguyen, Georg Pe- ' ters, Andrzej Skowron, Genlou Sun, Marcin Szczuka, Dominik Sl, ezak, Guoyin Wang, Hai Wang, Marcin Wolski, Haiyi Zhang, Yan Zhao, William Zhu. Their laudable e?orts made possible a careful selection and revision of submitted manuscripts.

This book constitutes the refereed proceedings of the International Conference on Brain Informatics, BI 2012, held in Macau, China, in December 2012. The 34 revised full papers were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on computer science, information technology, artificial intelligence, web intelligence, cognitive science, neuroscience, medical science, life science, economics, data mining, data and knowledge engineering, intelligent agent technology, human computer interaction, complex systems, and system science.

"Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state of the art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.