Due to measurement errors, transmission lost, or injected noise for privacy protection, uncertainty exists in the data of many real applications. However, query processing techniques for deterministic data cannot be directly applied to uncertain data because they do not have mechanisms to handle data uncertainty. Therefore, efficient and effective manipulation of uncertain data is a practical yet challenging research topic. In this book, we start from the data models for imprecise and uncertain data, move on to defining different semantics for queries on uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book serves as a comprehensive guideline for query processing over uncertain databases. Table of Contents: Introduction / Uncertain Data Models / Spatial Query Semantics over Uncertain Data Models / Spatial Query Processing over Uncertain Databases / Conclusion
Due to measurement errors, transmission lost, or injected noise for privacy protection, uncertainty exists in the data of many real applications. However, query processing techniques for deterministic data cannot be directly applied to uncertain data because they do not have mechanisms to handle data uncertainty. Therefore, efficient and effective manipulation of uncertain data is a practical yet challenging research topic. In this book, we start from the data models for imprecise and uncertain data, move on to defining different semantics for queries on uncertain data, and finally discuss the advanced query processing techniques for various probabilistic queries in uncertain databases. The book serves as a comprehensive guideline for query processing over uncertain databases. Table of Contents: Introduction / Uncertain Data Models / Spatial Query Semantics over Uncertain Data Models / Spatial Query Processing over Uncertain Databases / Conclusion
Introduction.- Uncertain Data Models.- Spatial Query Semantics over Uncertain Data Models.- Spatial Query Processing over Uncertain Databases.- Conclusion.
Lei Chen received a B.S. degree in Computer Science and Engineering from Tianjin University, China in 1994, an M.A. degree from Asian Institute of Technology, Thailand, in 1997, and a Ph.D. degree in Computer Science from University of Waterloo, Canada in 2005. He is now an associate professor in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology. His research interests include uncertain databases, graph databases, multimedia and time series databases, and sensor and peer-to-peer databases. He is serving as an associate editor forIEEETransaction on Knowledge and Data Engineering and Distributed and Parallel Databases. He is a member of the IEEE and ACM and chairman of ACM-HK Chapter Xiang Lian received a B.S. degree in 2003 from the Department of Computer Science and Technol ogy,Nanjing University,and a Ph.D.in 2009 from Hong Kong University of Science andTechnology, Hong Kong. He worked as a post-doctoral fellow in the Department of Computer Science and En gineering, at the Hong Kong University of Science and Technology in 2010 − 2011. He is now an assistant professor in the Department of Computer Science at University of Texas - Pan American. His research interests include query processing over probabilistic/uncertain databases, streaming time series, spatial databases, inconsistent probabilistic databases, and probabilistic RDF graphs. He is a student member of the IEEE
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