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

Dutta, Kaushik ; VanderMeer, Debra ; Datta, Anindya ; Keskinocak, Pinar ; Ramamritham, Krithi (2007) A fast method for discovering critical edge sequences in e-commerce catalogs European Journal of Operational Research, 181 (2). pp. 855-871. ISSN 0377-2217

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Official URL: http://www.sciencedirect.com/science/article/pii/S...

Related URL: http://dx.doi.org/10.1016/j.ejor.2006.06.055


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.

Item Type:Article
Source:Copyright of this article belongs to Elsevier Science.
Keywords:Data Mining; e-Commerce; Graph Theory; Applied Probability
ID Code:62885
Deposited On:24 Sep 2011 05:16
Last Modified:18 May 2016 11:57

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