'Uncertain data' diaporamas de présentation

COMP9315 Uncertain and Probabilistic Data

COMP9315 Uncertain and Probabilistic Data. Simplified version of SIGKDD08 by J. Pei, M. Hua, Y. Tao, X. Lin. Outline. Uncertainty and uncertain data, where and why? Models for uncertain and probabilistic data OLAP, Mining, and Queries on uncertain and probabilistic data.

1.35k views • 100 slides

Managing Uncertain Data

Managing Uncertain Data. Anish Das Sarma Stanford University. What is Uncertain Data?. Why Does It Arise?. Precision of devices. Lack of information. Uncertainty about the future. Anonymization. Applications: Information Extraction. Applications: Information Integration. name, hPhone,

812 views • 68 slides

Cleaning Uncertain Data for Top-k Queries

Cleaning Uncertain Data for Top-k Queries. Luyi Mo , Reynold Cheng, Xiang Li, David Cheung, Xuan Yang The University of Hong Kong { lymo , ckcheng , xli, dcheung , xyang2}@ cs.hku.hk. Outline. Introduction Quality Metric for Top-k Queries Definition Efficient computation Results

721 views • 54 slides

Cleaning Uncertain Data with Quality Guarantees

Very Large Database Conference 2008. Cleaning Uncertain Data with Quality Guarantees. Dr. Reynold Cheng Department of Computer Science The University of Hong Kong ckcheng@cs.hku.hk http://www.cs.hku.hk/~ckcheng/. A joint work with: Jinchuan Chen (Hong Kong Polytechnic University)

515 views • 51 slides

Probabilistic Data Management

Probabilistic Data Management. Chapter 2: Data Uncertainty Model. Objectives. In this chapter, you will: Learn the formal definition of uncertain data Explore different granularities of data uncertainty Become familiar with different representations of uncertain data

488 views • 48 slides

Robust Ranking of Uncertain Data

Robust Ranking of Uncertain Data. Da Yan and Wilfred Ng The Hong Kong University of Science and Technology. Outline. Background Probabilistic Data Model Related Work U-Pop k Semantics U-Pop k Algorithm Experiments Conclusion. Background.

506 views • 38 slides

Efficient Probabilistic Reverse Nearest Neighbor Query Processing on Uncertain Data

Efficient Probabilistic Reverse Nearest Neighbor Query Processing on Uncertain Data. Thomas Bernecker, Tobias Emrich , Hans-Peter Kriegel, Matthias Renz, Stefan Zankl and Andreas Zuefle. Outline. Background Uncertain Data Model Reverse k-nearest neighbour queries

345 views • 34 slides

Uncertainty Most intelligent systems have some degree of uncertainty associated with them.

Uncertainty Most intelligent systems have some degree of uncertainty associated with them. The types of uncertainty that can occur in KBS may be caused by problems with the data. 1. Data might be missing or unavailable.

686 views • 31 slides

UV-diagram: a Voronoi Diagram for uncertain data

26th IEEE International Conference on Data Engineering. UV-diagram: a Voronoi Diagram for uncertain data. Reynold Cheng (University of Hong Kong) Xike Xie (University of Hong Kong) Man Lung Yiu (Hong Kong Polytechnic University) Jinchuan Chen (Renmin University of China)

410 views • 29 slides

Sedimentation Data Analysis

551 views • 23 slides

Efficient summarization framework for multi-attribute uncertain data

369 views • 23 slides

Efficient Evaluation of Probabilistic Advanced Spatial Queries on Existentially Uncertain Data

Efficient Evaluation of Probabilistic Advanced Spatial Queries on Existentially Uncertain Data. By Man Lung Yiu, Nikos Mamoulis, Xiangyuan Dai, Yufei Tao, and Michail Vaitis. Presented By: John Burich CIS 601 Spring 2009. What the paper is about.

289 views • 20 slides

Chapter 13: Incorporating Uncertainty into Data Integration

Chapter 13: Incorporating Uncertainty into Data Integration. PRINCIPLES OF DATA INTEGRATION. ANHAI DOAN ALON HALEVY ZACHARY IVES. Outline. Sources of uncertainty in data integration Representing uncertain data (brief overview) Probabilistic schema mappings. Managing Uncertain Data.

328 views • 18 slides

PODS, May 23, 2012

Joint work with Pankaj K. Agarwal , Alon Efrat , and Swaminathan Sankararaman. Nearest-Neighbor Searching Under Uncertainty Wuzhou Zhang Department of Computer Science, Duke University. PODS, May 23, 2012. Nearest-Neighbor Searching. a set of points in. any query point in.

253 views • 18 slides

Frequent Itemset Mining of Uncertain Data Streams Using the Damped Window Model

Frequent Itemset Mining of Uncertain Data Streams Using the Damped Window Model. Carson Kai-Sang Leung, Fan Jiang SAC 2011. Outline. Motivation Background Method Experimental Result Conclusion. Motivation.

431 views • 17 slides

Constrained Frequent Itemset Mining from Uncertain Data Streams

Constrained Frequent Itemset Mining from Uncertain Data Streams. Carson Kai-Sang Leung, Boyu Hao , Fan Jiang ICDE 2010. outline. Motivation Method (UF-streaming+, UF-streaming * , CUF- streaming ) Experimental results Conclusion. motivation.

341 views • 13 slides

RAPID: Representation and Analysis of Probabilistic Intelligence Data

PAINT. RAPID: Representation and Analysis of Probabilistic Intelligence Data. Carnegie Mellon University PI : Prof. Jaime G. Carbonell / jgc@cs.cmu.edu / (412) 268-7279 Dr. Eugene Fink / e.fink@cs.cmu.edu / (412) 268-6593 Dr. Anatole Gershman / anatoleg@cs.cmu.edu / (412) 268-8259

188 views • 10 slides

Vienna, 11 th Nov 2013

Weaving Social Software Features Into Enterprise Resource Planning Systems Dirk Draheim Michael Felderer Viktor Pekar. draheim@acm.org michael.felderer@uibk.ac.at viktor.pekar@uibk.ac.at. Vienna, 11 th Nov 2013. Weaving Social Software Features into ERP Systems. Social Software.

83 views • 8 slides

Pankaj K. Agarwal , Alon Efrat , Swaminathan Sankararaman , and Wuzhou Zhang

PODS 2012. Nearest-Neighbor Searching Under Uncertainty. Motivation. 1. Squared Euclidean Distance. 3. Euclidean Metric (Approximate). Approximate by Outside the grid: Inside the grid : : center of cell Total # of cells :. : the centroid of Lemma:

138 views • 1 slides