PDF-Uncertain

BYomHaHuJudaisminanWorldWelcometothe20thannualOHALAHConferenceWelcometoour20tthannualgatheringMayyouarrivewithjoyousanticipationandcomeawaywithinspirationcreativepracticesrenewedprofessionalandpersona. R Petersen Uni ersity of Ne South ales at the Australian Defence orce Academy Ian Petersen is currently on secondment to the Australian Research Council brPage 2br Outline Introduction Perfect Re gulation with Norm Bounded Uncertainty The Main Resul 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 ifilmude Department of Computer Science University of Hong Kong nikoscshkuhk Department of Computer Science and Engineering Hong Kong University of Science and Technology leichencseusthk ABSTRACT Nearest neighbor NN queries in trajectory databases ha i64257lmude Department of Computer Science University of Hong Kong nikoscshkuhk ABSTRACT This paper targets the problem of computing meaningful clusterings from uncertain data sets Existing methods for clustering uncertain data compute a single clust 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. Robust Control Toolbox. Reza . Alinezhad. . Aliakbar. . Afzalian. . Jan 2012. 2. Reza Alinezhad Aliakbar Afzalian. Outline. Modeling uncertainty . Uncertain Elements. Uncertain . 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. 指導教授：陳良弼 老師. 報告者：鄧雅文 . 97753034. Introduction. Related Work. Problem Formulation. Future Work. Outline. Top-. k. query on certain data. Rank results according to a user-defined score. 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 . Wherever you roam. And admit that the waters. Around you have grown. And accept it that soon. You'll be drenched to the bone.. If your time to you. Is worth savin'. Then you better start swimmin'. Or you'll sink like a stone. 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.