- Full Description
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.
- Table of Contents
Table of Contents
- 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.
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