Efficient mining and prediction of user behavior patterns in mobile web systems

被引：71

作者：

Tseng, Vincent S. ^{[1
]}

Lin, Kawuu W. ^{[1
]}

机构：

[1] Natl Cheng Kung Univ, Inst Comp Sci & Informat Engn, Tainan 701, Taiwan

来源：

INFORMATION AND SOFTWARE TECHNOLOGY | 2006年 / 48卷 / 06期

关键词：

location-based services; location prediction; mobility prediction; mobile web system; data mining;

D O I：

10.1016/j.infsof.2005.12.014

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The development of wireless and web technologies has allowed the mobile users to request various kinds of services by mobile devices at anytime and anywhere. Helping the users obtain needed information effectively is an important issue in the mobile web systems. Discovery of user behavior can highly benefit the enhancements on system performance and quality of services. Obviously, the mobile user's behavior patterns, in which the location and the service are inherently coexistent, become more complex than those of the traditional web systems. In this paper, we propose a novel data mining method, namely SMAP-Mine that can efficiently discover mobile users' sequential movement patterns associated with requested services. Moreover, the corresponding prediction strategies are also proposed. Through empirical evaluation under various simulation conditions. SMAP-Mine is shown to deliver excellent performance in terms of accuracy, execution efficiency and scalability. Meanwhile. the proposed prediction strategies are also verified to be effective in measurements of precision, hit ratio and applicability. (C) 2006 Elsevier B.V. All rights reserved.

引用

页码：357 / 369

页数：13

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