'Web data' diaporamas de présentation

Managing Information Extraction SIGMOD 2006 Tutorial

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Internet Applications

Internet Applications. Chapter 7. Lecture Overview. Internet Concepts Web data formats HTML, XML, DTDs Introduction to three-tier architectures The presentation layer HTML forms; HTTP Get and POST, URL encoding; Javascript ; Stylesheets . XSLT The middle tier

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Learning Surface Text Patterns for a Question Answering System

Learning Surface Text Patterns for a Question Answering System Deepak Ravichandran Eduard Hovy Information Sciences Institute University of Southern California From Proceedings of the ACL Conference, 2002 Goal Explore power of surface text patterns for open-domain QA systems Why This Paper

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CS267 Applications of Parallel Computers Lecture 1: Introduction

CS267 Applications of Parallel Computers Lecture 1: Introduction. Horst D. Simon hdsimon@lbl.gov http://www.nersc.gov/~simon. Outline. Introduction Large important problems require powerful computers Why powerful computers must be parallel processors

1.01k views • 52 slides

Graph Clustering

Graph Clustering. Why graph clustering is useful?. Distance matrices are graphs ? as useful as any other clustering Identification of communities in social networks Webpage clustering for better data management of web data. Outline. Min s-t cut problem Min cut problem Multiway cut

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Restrict Range of Data Collection for Topic Trend Detection

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Random Forests for Language Modeling

Random Forests for Language Modeling. Peng Xu and Frederick Jelinek IPAM: January 24, 2006. What Is a Language Model?. A probability distribution over word sequences Based on conditional probability distributions: probability of a word given its history (past words). A. W*.

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Build data-driven collection and list apps using XAML

APP-912T. Build data-driven collection and list apps using XAML. Laurence Moroney Senior Program Manager Microsoft Corporation. Great apps are connected and alive with content and activity. Related sessions. [APP-737T] Metro Style Apps in XAML: What you need to know

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Evaluating Unsupervised Language Model Adaption Methods for Speaking Assessment

Evaluating Unsupervised Language Model Adaption Methods for Speaking Assessment. ShaSha Xie * Lei Chen Microsoft ETS 6/13/2013. Model Adaptation, Key to ASR Success. http://youtu.be/5FFRoYhTJQQ. Adaptation. Modern ASR systems are statistics-rich Acoustic model (AM) uses GMM or DNN

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SAMI: Situational Awareness from Multi-modal Input

SAMI: Situational Awareness from Multi-modal Input. Naveen Ashish. Talk Organization. Why are we at RESCUE interested ? Situational Awareness (SA) Introduction System architecture Research challenges Expected outcomes and artifacts Extraction system demonstration. Team. Bhaskar Rao

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Welcome to CPSC 404 Advanced Relational Databases

Welcome to CPSC 404 Advanced Relational Databases . Instructor : Laks V.S. Lakshmanan Email : laks@cs.ubc.ca Office : ICICS/CICSR 315-2366 Main Mall Lectures: M,W,F: 9-9:50 am, DMP 110. Office Hour: see http://www.cs.ubc.ca/~laks/404.html .

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Developing and Realizing Your Big Idea

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EMS/Trauma Registry Quarterly Update (June, July, August)

EMS/Trauma Registry Quarterly Update (June, July, August). August 13, 2013. What we will cover today:. Timeline for NTDB & NEMSIS File Implementation Trauma System Committee Registry Workgroup Recommended Reports RAC D Project Improvements Implemented. NTDB Implementation.

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Semantic Enablers for Next Generation Data Environments: Environmental and Disaster Data Focus

Semantic Enablers for Next Generation Data Environments: Environmental and Disaster Data Focus. Deborah L. McGuinness Tetherless World Senior Constellation Chair Professor of Computer and Cognitive Science Web Science Research Center Director Rensselaer Polytechnic Institute, Troy, NY

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The Web-DL Environment for Building Digital Libraries from the Web

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The Solomon Project in Brief (2007)

The Solomon Project in Brief (2007). Copy Detection. Static detection. Dynamic detection. Applications In Data Integration. Data fusion. Legend. Closed research. Ongoing research. New research. The Solomon Project in Brief (2008). Static detection. Copy Detection.

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Will new forms of data replace the survey: some provocations

Will new forms of data replace the survey: some provocations . www.cresc.ac.uk. Mike Savage CRESC & Sociology University of Manchester. Savage and Burrows 2007 argue.

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Mike Tung - founder+ceo

Mike Tung - founder+ceo. What is diffbot ?. We apply computer vision techniques to analyzing web pages, making web data useful for content applications. Technology Characteristics. Visual features Structural features Statistical classification Language-independent Formats-independent.

274 views • 7 slides