'Stream data' presentation slideshows

Data Mining with DB

Data Mining with DB. 14. Introduction to Data Mining. Motivation: Why data mining? What is data mining? Data Mining: On what kind of data? Data mining functionality Are all the patterns interesting? Classification of data mining systems Major issues in data mining.

1.89k views • 102 slides

Web data management Serge Abiteboul INRIA Saclay & ENS Cachan

613 views • 51 slides

IEEE 802.11 QoS MAC Enhancements Joint Proposal AT&T, Lucent, ShareWave

IEEE 802.11 QoS MAC Enhancements Joint Proposal AT&T, Lucent, ShareWave. Why Add QoS Support to the 802.11 MAC?. Why is it necessary to add new functionality within the 802.11 MAC sublayer to support QoS over wireless links? Higher layers assume that a LAN rarely loses or delays packets .

595 views • 50 slides

Introduction to Data Mining

792 views • 40 slides

LakeSuperiorStreams

http://LakeSuperiorStreams.org. Making stormwater and stream data come alive for citizens, students, teachers, contractors, resource agencies, decision-makers, and scientists.

455 views • 37 slides

Towards Linked Stream Data

Towards Linked Stream Data. Oscar Corcho. Contents. The concept of Linked Stream Data (LSD) Main challenges addressed so far W3C SSN Ontology URI definition Supporting technology Some examples Challenges being addressed currently. Linked Stream Data.

532 views • 37 slides

Smooth Streaming Live in HD 2010 Olympic Winter Games

Smooth Streaming Live in HD 2010 Olympic Winter Games. Scott Stanfield CEO Vertigo scott@vertigo.com. Bob Cowherd Olympics Project Lead Vertigo bob@vertigo.com. 2010 Vancouver Winter Olympic Games. Stats. Video 46 million total unique users 710 million page views

447 views • 35 slides

Introduction to Microsoft SQL Server 2008 R2 StreamInsight

PDC09-SVR07. Introduction to Microsoft SQL Server 2008 R2 StreamInsight. Torsten Grabs Senior Program Manager Lead Microsoft Corporation. What are Event-Driven Applications?. Event.

515 views • 30 slides

Database Systems

Database Systems. Lecture #1. Staff. Lecturer: Yael Amsterdamer http://www.cs.tau.ac.il/~yaelamst Schreiber, Databases lab, M-20, yaelamst@post Office hours: See web site. . tau.ac.il. Communications. Web page: http:// courses.cs.tau.ac.il/databases/databases201213b/

324 views • 27 slides

Computational Health Care

338 views • 26 slides

Classification and Novel Class Detection of Feature Based Stream Data.

Date : 21 st of May, 2014. Shri Ramdeo Baba College of Engineering and Management. Classification and Novel Class Detection of Feature Based Stream Data. A Technical Seminar on. Presentation By : Rimjhim Singh. Under the Guidance of: Dr. M.B. Chandak . Contents:.

361 views • 22 slides

A survey on stream data mining

370 views • 20 slides

A Distributed Framework for Collaborative Annotation of Streams

A Distributed Framework for Collaborative Annotation of Streams . Tao Huang, Shrideep Pallickara , Geoffrey Fox Community Grids Lab Indiana University, Bloomington { taohuang , spallick , gcf}@indiana.edu. Outline. Analysis of existing Collaboration and Annotation Systems

271 views • 17 slides

Chapter 10: Stream-based Data Management

Chapter 10: Stream-based Data Management. Title: Retrospective on Aurora Authors: Hari Balakrishnan, et. al. Design, Implementation, and Evaluation of the Linear Road Benchmark on the Stream Processing Core. Problem Problem Statement Why is this problem important?

277 views • 17 slides

Data Mining: Concepts and Techniques Mining data streams

Data Mining: Concepts and Techniques Mining data streams. Chapter 8. Mining Stream, Time-Series, and Sequence Data. Mining data streams Mining time-series data Mining sequence patterns in transactional databases Mining sequence patterns in biological data. Mining Data Streams.

646 views • 17 slides

GLEON Information Technology

280 views • 17 slides

247 views • 16 slides

Privacy Concerns

Privacy Concerns. Control over Collection Do customers know what information is being collected? Do customers feel they can decide upon the amount and type of information collected by retailers? Control over Use Do customers know how the information will be used by the retailer?

316 views • 15 slides

937 views • 9 slides

Redesign ideas

157 views • 9 slides