PPT-Query-Based Outlier Detection in Heterogeneous Information

Author : calandra-battersby | Published Date : 2016-10-31

Jonathan Kuck 1 Honglei Zhuang 1 Xifeng Yan 2 Hasan Cam 3 Jiawei Han 1 1 University of Illinois at UrbanaChampaign 2 University of California at Santa Barbara

Presentation Embed Code

Download Presentation

Download Presentation The PPT/PDF document "Query-Based Outlier Detection in Heterog..." is the property of its rightful owner. Permission is granted to download and print the materials on this website for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

Query-Based Outlier Detection in Heterogeneous Information: Transcript

Jonathan Kuck 1 Honglei Zhuang 1 Xifeng Yan 2 Hasan Cam 3 Jiawei Han 1 1 University of Illinois at UrbanaChampaign 2 University of California at Santa Barbara 3 US Army Research Lab. Yizhou. Sun, Rick Barber, Manish Gupta, . Charu. . C. . Aggarwal. , . Jiawei. Han. 1. Content. Background and motivation. Problem definition. PathPredict. : meta path-based . relationship prediction . Present and future. Outline. Outlier detection – types, editing, estimation. Description of the current method. Alternatives. Future work. Introduction of a new tool: R and . Rstudio. UNECE Statistical Data Editing 2014. DASFAA 2011. By. Hoang Vu Nguyen, . Vivekanand. . Gopalkrishnan. and Ira . Assent. Presented By. Salman. Ahmed . Shaikh. (D1). Contents. Introduction. Subspace Outlier Detection Challenges. Objectives of Research. Sarah Riahi and Oliver Schulte. School . of Computing Science. Simon Fraser University. Vancouver, Canada. With tools that you probably have around the . house. lab.. A simple method for multi-relational outlier detection. Detection. Carolina . Ruiz. Department of Computer Science. WPI. Slides based on . Chapter 10 of. “Introduction to Data Mining”. textbook . by Tan, Steinbach, Kumar. (all figures and some slides taken from this chapter. Gustavo Henrique Orair. Federal University of . Minas Gerais. Wagner Meira Jr.. Federal University of Minas Gerais. Presented by . Kajol. UH ID : 1358284. PURPOSE OF THE PAPER. Distance-Based . Yizhou. Sun, Rick Barber, Manish Gupta, . Charu. . C. . Aggarwal. , . Jiawei. Han. 1. Content. Background and motivation. Problem definition. PathPredict. : meta path-based . relationship prediction . Detection in Nonstationary . Time Series. Siqi. Liu. 1. , Adam Wright. 2. , and Milos Hauskrecht. 1. 1. Department of Computer Science, University of Pittsburgh. 2. Brigham and Women's Hospital and Harvard Medical School. Presented . by. Jeff . Bibeau. , Max Levine, . Jie. . Gao. Showcasing Work . by. . Milos . Hauskrecht. , . Iyad. . Batal. , Michal . Valko. , . Shyam. . Visweswaran. ,. Gregory F. Cooper, Gilles Clermont.. data mining approach . to flag unusual schools. Mayuko Simon. Data Recognition Corporation. May, 2012. 1. Statistical methods for data forensic. Univariate. distributional techniques: e.g., average wrong-to-right erasures.. Objective: develop technologies to improve computer performance. . . 1. Processor. Generation. Max. Clock. Speed (GHz). Max. Numberof Cores. Max. RAM. Bandwidth (GB/s). Max. Peak Floating Point (Gflop/s). Jian Pei. JD.com. & Simon Fraser University. Outlier Detection: Beauty and the Beast in Data Analytics. Subjectivity. Because of . …. Finding . Only Outliers Is . Not Useful. Every outlier detection algorithm bears some “model(s)” in mind. Fanjin. Zhang, Xiao Liu, . Jie. Tang, . Yuxiao. Dong, . Peiran. Yao, . Jie. Zhang, . Xiaotao. Gu, Yan Wang, Bin Shao, Rui Li and . Kuansan. Wang.. Tsinghua University Microsoft Research. Course Goal. The goal of this course is to teach end users of ctcLink PeopleSoft to find and retrieve Queries and Reports in the most effective manner.. Course Learning Objectives. At the end of this course users will:.

Download Document

Here is the link to download the presentation.
"Query-Based Outlier Detection in Heterogeneous Information"The content belongs to its owner. You may download and print it for personal use, without modification, and keep all copyright notices. By downloading, you agree to these terms.