基于作者主题模型和辐射模型的用户位置预测模型

doi:10.11772/j.issn.1001-9081.2017102539

计算机应用 ›› 2018, Vol. 38 ›› Issue (4): 939-944.DOI: 10.11772/j.issn.1001-9081.2017102539

基于作者主题模型和辐射模型的用户位置预测模型

李琰, 刘嘉勇

四川大学电子信息学院, 成都 610065

收稿日期:2017-10-26 修回日期:2017-12-07 出版日期:2018-04-10 发布日期:2018-04-09
通讯作者: 李琰
作者简介:李琰(1993-),女,贵州镇远人,硕士研究生,主要研究方向:数据挖掘、位置预测;刘嘉勇(1962-),男,四川成都人,教授,博士,主要研究方向:信息安全、网络信息处理、信息安全。

User location prediction model based on author topic model and radiation model

LI Yan, LIU Jiayong

College of Electronics and Information Engineering, Sichuan University, Chengdu Sichuan 610065, China

Received:2017-10-26 Revised:2017-12-07 Online:2018-04-10 Published:2018-04-09

摘要/Abstract

摘要： 由于全球定位系统（GPS）设备采集的用户历史位置数据通常具有稀疏性，使得基于单个用户数据的位置预测模型能力受限，所以结合人类移动性的时间和空间周期性，提出一种基于作者主题模型（ATM）和辐射模型（RM）的用户位置预测模型。在时间维度上，该模型利用ATM发现与目标用户移动行为相似的用户群，并确定该用户群在预测时刻所处的目标状态；在空间维度上，该模型利用RM算法计算目标用户的候选地点在目标状态下的概率，并通过比较各候选地点的概率值确定目标用户可能出现的地点，从而实现对目标用户位置的预测。实验结果表明，该模型的平均预测准确率为61.49%，相对于基于变阶的Markov模型提高近28个百分点。所提预测模型能够在单个用户数据量小的条件下获得更高的预测准确率。

关键词: 人类移动性, 基于位置的服务, 作者主题模型, 辐射模型, 位置预测

Abstract: Due to the sparseness of user's historical location data collected by Global Positioning System (GPS) devices, the capability of location prediction model based on single user data was limited. Therefore, a new user location prediction model based on Author Topic Model (ATM) and Radiation Model (RM) was proposed. In the time dimension, the user group that similar to the target user was discovered by using ATM, and the target state of the user group at the prediction time was determined. In the spatial dimension, the RM algorithm was used to calculate the probabilities of target user's candidate location in the target state, and the user's target predictive location could be achieved by comparing the probability value of each candidate location to determine the location where the target user might occur. The experimental results show that the average prediction accuracy of the model is 61.49%, which is nearly 28 percentage points higher than that of the Markov model based on variable order. The proposed model can obtain higher prediction accuracy under the condition of small amount of single user data.

Key words: human mobility, Location Based Service (LBS), Author Topic Model (ATM), Radiation Model (RM), location prediction

中图分类号:

TP311

李琰, 刘嘉勇. 基于作者主题模型和辐射模型的用户位置预测模型[J]. 计算机应用, 2018, 38(4): 939-944.

LI Yan, LIU Jiayong. User location prediction model based on author topic model and radiation model[J]. Journal of Computer Applications, 2018, 38(4): 939-944.

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基于作者主题模型和辐射模型的用户位置预测模型

User location prediction model based on author topic model and radiation model

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