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Engineering - Computational Intelligence and Complexity | Advances in Probabilistic Databases for Uncertain Information Management

Advances in Probabilistic Databases for Uncertain Information Management

Ma, Zongmin, Yan, Li (Eds.)

2013, X, 161 p. 23 illus.

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  • Covers a fast-growing topic in great depth
  • Focuses on the technologies and applications of the probabilistic databases for uncertain data management
  • State-of-the-art book

This book covers a fast-growing topic in great depth and focuses on the technologies and applications of probabilistic data management. It aims to provide a single account of current studies in probabilistic data management. The objective of the book is to provide the state of the art information to researchers, practitioners, and graduate students of information technology of intelligent information processing, and at the same time serving the information technology professional faced with non-traditional applications that make the application of conventional approaches difficult or impossible.

Content Level » Research

Keywords » Probabilistic Databases - Soft Computing - Web Intelligence - XML

Related subjects » Artificial Intelligence - Computational Intelligence and Complexity - Database Management & Information Retrieval

Table of contents 

1   Research in Probabilistic Spatiotemporal Databases:
The SPOT Framework.-

2   A Probabilistic Object-Oriented Database Model with
Fuzzy Measures.-

3   Probabilistic XML: Models and Complexity.-

4   Uncertain Data: Representations, Query Processing,
and Applications.-

5   A Theoretically-Sound Approach for OLAPing Uncertain
and Imprecise Multidimensional Data Streams.-

6   Tractable Probabilistic Description Logic Programs.  

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