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which remainsexactly the same through time As usual we let the player set be I1. unip dit Abstract Preferences and uncertain ccur in man reallife problems The theory of ossibilit is one nonprobabilistic of dealing with un certain whic allo ws for easy in tegration with fuzzy preferences In this pap er consider an existing tec hni usthk lifeifeicsfsuedu gkollioscsbuedu diveshresearchattcom Abstract This ork intr oduces no el polynomialtime al gorithms or pr ocessing top queries in uncertain databases under the generally adopted model of xr elations An xr elation consists of nu Cockburn b Srinivas Palanki aDepartment of Chemical Engineering Florida UniversityFlorida State University 2525 Pottsdamer Street Tallahassee FL 323106046 USA bDepartment of Electrical Engineering Florida UniversityFlorida State University 2525 Pot Volume. Temperature. Mass. Reading the Meniscus. Always read volume from the bottom of the . meniscus. . The meniscus is the curved surface of a liquid in a narrow cylindrical container.. Try to avoid parallax errors.. Doug Burdick, Prasad Deshpande, T. S. . Jayram. , . Raghu . Ramakrishnan. , . Shivakumar. . Vaithyanathan. Presented by . Raghav. . Sagar. OLAP Overview. Online Analytical Processing (OLAP). Interactive analysis of data, allowing data to be summarized and viewed in different ways in an online . School of Computing. National University of Singapore. Department of Computer Science. Aalborg. University. Meihui. Zhang. , Su Chen, Christian S. Jensen, . Beng. Chin . Ooi. , . Zhenjie. Zhang. Data Uncertainty: . Modeling and Querying. Mohamed F. Mokbel. Department of Computer Science and Engineering. University of Minnesota. www.cs.umn.edu/~mokbel. mokbel@cs.umn.edu. 2. Talk Outline. Introduction to Uncertain Data. School of Computing. National University of Singapore. Department of Computer Science. Aalborg. University. Meihui. Zhang. , Su Chen, Christian S. Jensen, . Beng. Chin . Ooi. , . Zhenjie. Zhang. Arijit Khan. Systems Group. ETH Zurich. Lei Chen. Hong . Kong University of Science and Technology. Social Network. Transportation Network. Chemical Compound. Biological Network. Graphs are Everywhere. Chapter 1: An Overview of Probabilistic Data Management. 2. Objectives. In this chapter, you will:. Get to know what uncertain data look like. Explore causes of uncertain data in different applications. Chapter 3: Probabilistic Query Answering (1). 2. Objectives. In this chapter, you will:. Learn the challenge of probabilistic query answering on uncertain data. Become familiar with the . framework for probabilistic . Chapter 3: Probabilistic Query Answering (1). 2. Objectives. In this chapter, you will:. Learn the challenge of probabilistic query answering on uncertain data. Become familiar with the . framework for probabilistic . Data Uncertainty: . Modeling and Querying. Mohamed F. Mokbel. Department of Computer Science and Engineering. University of Minnesota. www.cs.umn.edu/~mokbel. mokbel@cs.umn.edu. 2. Talk Outline. Introduction to Uncertain Data. Chapter 7: Probabilistic Query Answering (5). 2. Objectives. In this chapter, you will:. Explore the definitions of more probabilistic query types. Probabilistic skyline query. Probabilistic reverse skyline query.