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Managing and Mining Uncertain Data / edited by Charu C. Aggarwal
Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Advances in Database Systems ; 35 | SpringerLink BücherPublisher: Boston, MA : Springer-Verlag US, 2009Edition: 1Description: Online-Ressource (XXII, 494p. 60 illus, digital)ISBN:- 9780387096902
- 006.312
- Q375
Contents:
Summary: 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. TOC:Preface.- Introduction.- Uncertain Data Management: Introduction.- Models for Incomplete and Probabilistic Information.- Probabilistic and Relational Models with Uncertain Data.- ULDB and the Trio System.- Indexing Uncertain Data.- Probabilistic Graphical Models.- Query Evaluation for Uncertain Data.- Clustering Uncertain Data.- Classification of Uncertain Data.- Sketching Probabilistic Data.- Uncertain Spatio-temporal Applications.- Uncertain Representations and Applications in Sensor Networks.- OLAP over Uncertain data.- Index.PPN: PPN: 1649887930Package identifier: Produktsigel: ZDB-2-SCS
Preface; Contents; List of Figures; List of Tables; Chapter 1 AN INTRODUCTION TO UNCERTAIN DATA ALGORITHMS AND APPLICATIONS; Chapter 2 MODELS FOR INCOMPLETE AND PROBABILISTIC INFORMATION; Chapter 3 RELATIONAL MODELS AND ALGEBRA FOR UNCERTAIN DATA; Chapter 4 GRAPHICAL MODELS FOR UNCERTAIN DATA; Chapter 5 TRIO:ASYSTEMFORDATA,UNCERTAINTY,AND LINEAGE; Chapter 6 MAYBMS: A SYSTEM FOR MANAGING LARGE UNCERTAIN AND PROBABILISTIC DATABASES; Chapter 7 UNCERTAINTY IN DATA INTEGRATION; Chapter 8 SKETCHING AGGREGATES OVER PROBABILISTIC STREAMS; Chapter 9 PROBABILISTIC JOIN QUERIES IN UNCERTAIN DATABASES
Chapter 10 INDEXING UNCERTAIN DATAChapter 11 RANGEANDNEARESTNEIGHBORQUERIESON UNCERTAIN SPATIOTEMPORAL DATA; Chapter 12 PROBABILISTIC XML; Chapter 13 ON CLUSTERING ALGORITHMS FOR UNCERTAIN DATA; Chapter 14 ON APPLICATIONS OF DENSITY TRANS FORMSFOR UNCERTAIN DATA MINING; Chapter 15 FREQUENT PATTERN MINING ALGORITHMS WITH UNCERTAIN DATA; Chapter 16 PROBABILISTIC QUERYING AND MINING OF BIOLOGICAL IMAGES; Index
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