By Topic

webSPADE: a parallel sequence mining algorithm to analyze web log data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
A. Demiriz ; Inf. Technol., Verizon Inc., Irving, TX, USA

Enterprise-class web sites receive a large amount of traffic, from both registered and anonymous users. Data warehouses are built to store and help analyze the click streams within this traffic to provide companies with valuable insights into the behavior of their customers. This article proposes a parallel sequence mining algorithm, webSPADE, to analyze the click streams found in site web logs. In this process, raw web logs are first cleaned and inserted into a data warehouse. The click streams are then mined by webSPADE. An innovative web-based front-end is used to visualize and query the sequence mining results. The webSPADE algorithm is currently used by Verizon to analyze the daily traffic of the web site.

Published in:

Data Mining, 2002. ICDM 2003. Proceedings. 2002 IEEE International Conference on

Date of Conference: