Jan Komorowski

Jan Zytkow

This book constitutes the refereed proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD '97, held in Trondheim, Norway, in June 1997. The volume presents a total of 38 revised full papers together with abstracts of one invited talk and four tutorials. Among the topics covered are data and knowledge representation, statistical and probabilistic methods, logic-based approaches, man-machine interaction aspects, AI contributions, high performance computing support, machine learning, automated scientific discovery, quality assessment, and applications.

First European Symposium, PKDD '97, Trondheim, Norway, June 24-27, 1997 Proceedings

Principles of Data Mining and Knowledge Discovery

This volume contains papers selected for presentation at the Seventh International Symposium on Methodologies for Intelligent Systems (ISMIS '93), held at the Norwegian Institute of Technology, Trondheim, Norway, in June 1993. The volume includes six invited talks and 43 contributed papers organized under the following headings: logic for artificial intelligence, expert systems, intelligent databases, approximate reasoning, constraint programming, learning and adaptive systems, methodologies, knowledge representation, and manufacturing. Theinvited talks are: "On extended disjunctive logic programs" (J. Minker, C. Ruiz), "Towards intelligent databases" (F. Bry), "Methodologies for knowledge-based software engineering" (M. Lowry), "Modelling of industrial systems" (L. Ljung), "The many faces of inductive logic programming" (L. De Raedt, N. Lavrac), and "Systematic assessment of temporal reasoning methods for use in autonomous agents" (E. Sandewall).

7th International Symposium, ISMIS'93, Trondheim, Norway, June 15-18, 1993. Proceedings

Methodologies for Intelligent Systems

Roman Slowiński

Shusaku Tsumoto

Jerzy W. Grzymala-Busse

In recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining.

4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5, 2004, Proceedings

Rough Sets and Current Trends in Computing

Djamel A. Zighed

This book constitutes the refereed proceedings of the 4th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2000, held in Lyon, France in September 2000. The 86 revised papers included in the book correspond to the 29 oral presentations and 57 posters presented at the conference. They were carefully reviewed and selected from 147 submissions. The book offers topical sections on new directions, rules and trees, databases and reward-based learning, classification, association rules and exceptions, instance-based discovery, clustering, and time series analysis.

Jan Komorowski

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