Indexing and Mining Time Sequences

author: Christos Faloutsos, Computer Science Department, Carnegie Mellon University
author: Lei Li, Computer Science Department, Carnegie Mellon University
published: Oct. 1, 2010,   recorded: July 2010,   views: 7651
Categories

Slides

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 1:11:16
!NOW PLAYING
Watch Part 2
Part 2 31:30
!NOW PLAYING
Watch Part 3
Part 3 36:15
!NOW PLAYING

Description

How can we find patterns in a sequence of sensor measurements (eg., a sequence of temperatures, or water-pollutant measurements)? How can we compress it? What are the major tools for forecasting and outlier detection? The objective of this tutorial is to provide a concise and intuitive overview of the most important tools that can help us find patterns in sensor sequences. Sensor data analysis becomes of increasingly high importance, thanks to the decreasing cost of hardware and the increasing on-sensor processing abilities. We review the state of the art in three related fields: (a) fast similarity search for time sequences, (b) linear forecasting with the traditional AR (autoregressive) and ARIMA methodologies, (c) non-linear forecasting, for chaotic/self-similar time sequences, using lag-plots and fractals, and (d) Kalman filters. The emphasis of the tutorial is to give the intuition behind these powerful tools, which is usually lost in the technical literature, as well as to give case studies that illustrate their practical use.

See Also:

Download slides icon Download slides: kdd2010_faloutsos_li_imt.pdf (4.9┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 Abdul Wahab , November 16, 2010 at 3:58 p.m.:

Which Software/tool is used for the graphs shown in this video ?

Write your own review or comment:

make sure you have javascript enabled or clear this field: