Ebook: Managing and Mining Uncertain Data

Managing and Mining Uncertain Data contains surveys by well known researchers in the field of uncertain databases. The book presents the most recent models, algorithms, and applications in the uncertain data field in a structured and concise way. This book is organized so as to cover the most important management and mining topics in the field. The idea is to make it accessible not only to researchers, but also to application-driven practitioners for solving real problems. Given the lack of structurally organized information on the new and emerging area of uncertain data, this book provides insights which are not easily accessible elsewhere.

Managing and Mining Uncertain Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level database students in computer science and engineering.

Editor Biography

Charu C. Aggarwal obtained his B.Tech in Computer Science from IIT Kanpur in 1993 and Ph.D. from MIT in 1996. He has been a Research Staff Member at IBM since then, and has published over 120 papers in major conferences and journals in the database and data mining field. He has applied for or been granted over 65 US and International patents, and has thrice been designated Master Inventor at IBM for the commercial value of his patents. He has been granted 17 invention achievement awards by IBM for his patents. His work on real time bio-terrorist threat detection in data streams won the IBM Corporate award for Environmental Excellence in 2003. He is a recipient of the IBM Outstanding Innovation Award in 2008 for his scientific contributions to privacy technology, and a recipient of the IBM Research Division award for his contributions to stream mining for the System S project. He has served on the program committee of most major database conferences, and was program chair for the Data Mining and Knowledge Discovery Workshop, 2003, and program vice-chairs for the SIAM Conference on Data Mining 2007, ICDM Conference 2007, and the WWW Conference, 2009. He served as an associate editor of the IEEE Transactions on Data Engineering from 2004 to 2008. He is an associate editor of the ACM SIGKDD Explorations and an action editor of the Data Mining and Knowledge Discovery Journal. He is a senior member of the IEEE and a life-member of the ACM.

Fuzzy Database Modeling with XML aims to provide a single record of current research and practical applications in the fuzzy databases. This volume is the outgrowth of research the author has conducted in recent years. Fuzzy Database Modeling with XML introduces state-of-the-art information to the database research, while at the same time serving the information technology professional faced with a non-traditional application that defeats conventional approaches.

The research on fuzzy conceptual models and fuzzy object-oriented databases is receiving increasing attention, in addition to fuzzy relational database models. With rapid advances in network and internet techniques as well, the databases have been applied under the environment of distributed information systems. It is essential in this case to integrate multiple fuzzy database systems. Since databases are commonly employed to store and manipulate XML data, additional requirements are necessary to model fuzzy information with XML. Secondly, this book maps fuzzy XML model to the fuzzy databases. Very few efforts at investigating these issues have thus far occurred.

Fuzzy Database Modeling with XML is designed for a professional audience of researchers and practitioners in industry. This book is also suitable for graduate-level students in computer science.