By Topic

Sequence Mining for User Behavior Patterns in Mobile Commerce

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
$31 $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

2 Author(s)
Yu Ning ; Sch. of Manage. Sci. & Eng., Beijing Univ. of Posts & Telecommun., Beijing ; Hongbin Yang

User behavior patterns is one of the most essential issues that need to be explored in mobile commerce. In this paper, we propose a new algorithm can efficiently discover mobile users' sequential movement patterns associated in a personal communication systems network. In the first phase of our three phase algorithm, user mobility patterns are mined from the history of mobile user trajectories. In the second phase, mobility rules are extracted from these patterns, and in the last phase, mobility predictions are accomplished by using these rules. The performance results obtained in terms of precision and recall indicate that our method can make more accurate predictions than the other methods.

Published in:

Management of e-Commerce and e-Government, 2008. ICMECG '08. International Conference on

Date of Conference:

17-19 Oct. 2008