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A fast method for discovering critical edge sequences in e-commerce catalogs

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Title A fast method for discovering critical edge sequences in e-commerce catalogs
 
Creator DUTTA, KAUSHIK
VANDERMEER, DEBRA
DATTA, ANINDYA
KESKINOCAK, PINAR
RAMAMRITHAM, KRITHI
 
Subject data mining
electronic commerce
customer satisfaction
data storage equipment
graph theory
 
Description Web sites allow the collection of vast amounts of navigational data – clickstreams of user traversals through the site. These massive data stores offer the tantalizing possibility of uncovering interesting patterns within the dataset. For e-businesses, always looking for an edge in the hyper-competitive online marketplace, the discovery of critical edge sequences (CESs), which denote frequently traversed sequences in the catalog, is of significant interest. CESs can be used to improve site performance and site management, increase the effectiveness of advertising on the site, and gather additional knowledge of customer behavior patterns on the site.
Using web mining strategies to find CESs turns out to be expensive in both space and time. In this paper, we propose an approximate algorithm to compute the most popular traversal sequences between node pairs in a catalog, which are then used to discover CESs. Our method is both fast and space efficient, providing a vast reduction in both the run time and storage requirements, with minimum impact on accuracy.
 
Publisher Elsevier
 
Date 2009-05-08T02:35:08Z
2011-12-08T06:55:32Z
2011-12-26T13:01:52Z
2011-12-27T05:47:27Z
2009-05-08T02:35:08Z
2011-12-08T06:55:32Z
2011-12-26T13:01:52Z
2011-12-27T05:47:27Z
2007
 
Type Article
 
Identifier European Journal of Operational Research 181(2), 855-871
0377-2217
10.1016/j.ejor.2006.06.055
http://hdl.handle.net/10054/1299
http://dspace.library.iitb.ac.in/xmlui/handle/10054/1299
 
Language en