基于用户位置的频繁轨迹模式挖掘
Frequent Trajectory Pattern Mining Based on User Location
任建宇 1龚亚奇 1张祯2
作者信息
- 1. 沈阳化工大学 计算机科学与技术学院,辽宁 沈阳 110142
- 2. 营口理工学院 电气工程学院,辽宁 营口 115014
- 折叠
摘要
近年来,从大量的频繁轨迹数据中提取有用信息以提供更佳的用户服务已成为一项重要挑战.其中涉及了信息的冗余和浪费,以及数据利用不充分的问题,这些因素导致了较低的数据利用率和算法效率.针对这些问题,文章深入分析了用户轨迹模式的挖掘方法.采用网格划分方法以及经过改进的Apriori算法,能够在高效且充分利用数据的前提下,快速有效地挖掘出用户的频繁路径模式.
Abstract
In recent years,extracting useful information from large amounts of frequent trajectory data to provide better user service has become an important challenge.It involves the redundancy and waste of information,as well as the problem of insufficient data utilization,which leads to low data utilization and algorithm efficiency.Aiming at these problems,this paper deeply analyzes the mining method of user trajectory pattern.By using the grid partitioning method and the improved Apriori algorithm,users'frequent path patterns can be mined quickly and effectively under the premise of efficient and full use of data.
关键词
位置社交网络/频繁轨迹/数据挖掘Key words
location social network/frequent trajectory/data mining引用本文复制引用
出版年
2024
NETL
NSTL
维普
万方数据