Transactions on Rough Sets I

The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, starting from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence.
This first volume of the Transactions on Rough Sets opens with an introductory article by Zdzislaw Pawlak, the originator of rough sets. Nine papers deal with rough set theory and eight are devoted to applications in various domains.

Rough Sets – Introduction.- Some Issues on Rough Sets.- Rough Sets – Theory.- Learning Rules from Very Large Databases Using Rough Multisets.- Data with Missing Attribute Values: Generalization of Indiscernibility Relation and Rule Induction.- Generalizations of Rough Sets and Rule Extraction.- Towards Scalable Algorithms for Discovering Rough Set Reducts.- Variable Precision Fuzzy Rough Sets.- Greedy Algorithm of Decision Tree Construction for Real Data Tables.- Consistency Measures for Conflict Profiles.- Layered Learning for Concept Synthesis.- Basic Algorithms and Tools for Rough Non-deterministic Information Analysis.- A Partition Model of Granular Computing.- Rough Sets – Applications.- Musical Phrase Representation and Recognition by Means of Neural Networks and Rough Sets.- Processing of Musical Metadata Employing Pawlak’s Flow Graphs.- Data Decomposition and Decision Rule Joining for Classification of Data with Missing Values.- Rough Sets and Relational Learning.- Approximation Space for Software Models.- Application of Rough Sets to Environmental Engineering Models.- Rough Set Theory and Decision Rules in Data Analysis of Breast Cancer Patients.- Independent Component Analysis, Principal Component Analysis and Rough Sets in Face Recognition.