An efficient method for mining associated service patterns in mobile web environments

Vincent Shin-Mu Tseng*, Cing Fu Tsui

*此作品的通信作者

研究成果: Paper同行評審

8 引文 斯高帕斯(Scopus)

摘要

This research presents a new data mining method that can efficiently discover associated service patterns requested by users in mobile web environments. Although there exist some studies on data mining in mobile systems in recent years, they were mostly focused on topics like moving path mining or service request log mining and the issue of discovering user's associated service patterns with the locations has not been explored. In particular, this problem becomes more complex when the hierarchical concepts of locations and services are considered. In this work, we propose a new data mining method named two-dimensional multi-level association rules mining, which can efficiently discover the associated service request patterns by taking into account the hierarchical characteristics of the location and service concept. To our best knowledge, this is the first work resolving this research issue. Through detailed experimental evaluations under various system conditions, our method was shown to deliver excellent performance in terms of accuracy, completeness, execution efficiency and scalability.

原文English
頁面455-459
頁數5
DOIs
出版狀態Published - 18 7月 2003
事件Proceedings of the 2003 ACM Symposium on Applied Computing - Melbourne, FL, United States
持續時間: 9 3月 200312 3月 2003

Conference

ConferenceProceedings of the 2003 ACM Symposium on Applied Computing
國家/地區United States
城市Melbourne, FL
期間9/03/0312/03/03

指紋

深入研究「An efficient method for mining associated service patterns in mobile web environments」主題。共同形成了獨特的指紋。

引用此