Rough Sets

Rough-set theory has become well established since first introduced by Pawlak in the 1970s. It is based on two simple concepts: indiscernibility and approximation regions. Rough-set theory is a formal theory, mathematically sound. It has been applied to several areas of research such as logic and knowledge discovery, and has been implemented in various applications in the real world. Because of rough sets’ ability to define uncertain things in terms of certain, definable things, it is a natural mechanism for integrating real-world uncertainty in computerized databases. Moreover, other uncertainty-management techniques may be combined with rough sets to offer even greater uncertainty management in databases. This chapter discusses how rough-sets AbstrAct

[1]  Antonio Cartelli.  Open Source Software and Information Systems on the Web , 2005, Encyclopedia of Database Technologies and Applications.

[2]  Ramayya Krishnan,et al.  CMU-WEB: A Conceptual Model for Designing Usable Web Applications , 1999, J. Database Manag..

[3]  Emmanuel Udoh.  Open Source Database Technologies , 2009, Database Technologies: Concepts, Methodologies, Tools, and Applications.

[4]  Venkataraman Ramesh,et al.  Human Factors Research on Data Modeling: A Review of Prior Research, An Extended Framework and Future Research Directions , 2002, J. Database Manag..

[5]  John S. Erickson.  Database Technologies: Concepts, Methodologies, Tools, and Applications (4 Volumes) , 2009, Database Technologies: Concepts, Methodologies, Tools, and Applications.

[6]  Rajkumar Buyya,et al.  Service Level Agreement (SLA) in Utility Computing Systems , 2010, ArXiv.

[7]  Frédérique Laforest,et al.  Using Weakly Structured Documents to Fill in a Classical Database , 2001, J. Database Manag..

[8]  Ruppa K. Thulasiram,et al.  Performance Analysis of Sequential and Parallel Neural Network Algorithm for Stock Price Forecasting , 2011, Int. J. Grid High Perform. Comput..

[9]  Xuelong Li,et al.  Semantic Mining Technologies for Multimedia Databases , 2009 .

[10]  Salvatore T. March,et al.  Modeling Temporal Dynamics for Business Systems , 2003, J. Database Manag..

[11]  Mario Piattini,et al.  Fuzzy Aggregations and Fuzzy Specializations in Eindhoven Fuzzy EER Model , 2004, Advanced Topics in Database Research, Vol. 3.

[12]  R. Nedunchezhian,et al.  Soft Computing Applications for Database Technologies: Techniques and Issues , 2010 .

[13]  Keng Siau,et al.  Advanced Topics In Database Research , 2005 .

[14]  Philip Calvert,et al.  Encyclopedia of Database Technologies and Applications , 2005 .

[15]  Peter Danielson.  Metaphors and Models for Data Mining Ethics , 2009, Database Technologies: Concepts, Methodologies, Tools, and Applications.

[16]  Veda C. Storey,et al.  The Quality of Online Privacy Policies: A Resource-Dependency Perspective , 2009, J. Database Manag..

[17]  Kees van Slooten,et al.  On the Adaptation of an Agile Information Systems Development Method , 2005, J. Database Manag..

[18]  Hong Va Leong.  Transactional Support for Mobile Databases , 2005, Encyclopedia of Database Technologies and Applications.

[19]  Wen Gao,et al.  Semantic Classification and Annotation of Images , 2009, Semantic Mining Technologies for Multimedia Databases.

[20]  Iris Reinhartz-Berger,et al.  Semi-Automatic Composition of Situational Methods , 2011, J. Database Manag..