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Managing and Mining Uncertain Data de Charu C. Aggarwal

Managing and Mining Uncertain Data: Advances in Database Systems, cartea 35

Editat de Charu C. Aggarwal
en Limba Engleză Paperback – 6 dec 2010
Managing and Mining Uncertain Data, a survey with chapters by a variety of well known researchers in the data mining field, presents the most recent models, algorithms, and applications in the uncertain data mining field in a structured and concise way. This book is organized to make it more accessible to applications-driven practitioners for solving real problems. Also, given the lack of structurally organized information on this topic, Managing and Mining Uncertain Data provides insights which are not easily accessible elsewhere. Managing and Mining Uncertain Data is designed for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference book for advanced-level students in computer science and engineering, as well as the ACM, IEEE, SIAM, INFORMS and AAAI Society groups.
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Specificații

ISBN-13: 9781441935175
ISBN-10: 1441935177
Pagini: 516
Ilustrații: XXII, 494 p. 60 illus.
Dimensiuni: 155 x 235 x 27 mm
Greutate: 0.72 kg
Ediția:Softcover reprint of hardcover 1st ed. 2009
Editura: Springer Us
Colecția Springer
Seria Advances in Database Systems

Locul publicării:New York, NY, United States

Public țintă

Professional/practitioner

Cuprins

An Introduction to Uncertain Data Algorithms and Applications.- Models for Incomplete and Probabilistic Information.- Relational Models and Algebra for Uncertain Data.- Graphical Models for Uncertain Data.- Trio A System for Data Uncertainty and Lineage.- MayBMS A System for Managing Large Probabilistic Databases.- Uncertainty in Data Integration.- Sketching Aggregates over Probabilistic Streams.- Probabilistic Join Queries in Uncertain Databases.- Indexing Uncertain Data.- Querying Uncertain Spatiotemporal Data.- Probabilistic XML.- On Clustering Algorithms for Uncertain Data.- On Applications of Density Transforms for Uncertain Data Mining.- Frequent Pattern Mining Algorithms with Uncertain Data.- Probabilistic Querying and Mining of Biological Images.

Recenzii

From the reviews:
"The three broad areas covered in Aggarwal’s book are modeling and system design, management, and mining of uncertain data. … Aggarwal’s book is a timely publication, in that it provides a good summary of the current state of the art in the area of uncertain data modeling, management, and mining. It should be of interest to researchers and graduate students involved in the area, as well as novices who wish to become acquainted with the topic." (John Fulcher, ACM Computing Reviews, May, 2009)

Textul de pe ultima copertă

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.

Caracteristici

Survey information included with each chapter is unique in terms of introducing the different topics more comprehensively Includes case studies based on real-world examples