Earticle

초록

영어

Recently, the study of smart phone user habits has become a highly focused topic due to the rapid growth of the smart phone market. Indeed, sequential pattern analysis methods were efficiently used for web-based user habit mining long time ago. However, by means of simulations, it has been observed that these methods might fail for smart phone-based user habit mining. In this paper, we propose a novel approach that leads to a considerably increased performance of the traditional sequential pattern analysis methods by reasonably cutting off each chronological sequence of user logs on a device into shorter ones, which represent the sequential user activities in various periods of a day.

목차

Abstract
 1. Introduction
 2. Related works
 3. A method for detecting frequent sequential log patterns
 4. Conclusion
 References

키워드

저자

• Lu Dang Nhac [ Academy of Journalism and Communication ]
• Nguyen Thu Trang [ University of Engineering and Technology, Vietman National University in Hanoi ]
• Nauyen Thi Hau [ University of Engineering and Technology, Vietman National University in Hanoi ]
• Nguyen Ha Nam [ University of Engineering and Technology, Vietman National University in Hanoi ]
• Gyoo Seok Choi [ Departmant of Computer Science, Chungwoon University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Internet, Broadcasting and Communication

• 간기

  계간

• pISSN

  2288-4920

• eISSN

  2288-4939

• 수록기간

  2009~2025

• 십진분류

  KDC 326 DDC 380