Next place prediction using mobility Markov chains

MPM '12 Pub Date : 2012-04-10 DOI:10.1145/2181196.2181199
S. Gambs, M. Killijian, Miguel Núñez del Prado Cortez
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引用次数: 499

Abstract

In this paper, we address the issue of predicting the next location of an individual based on the observations of his mobility behavior over some period of time and the recent locations that he has visited. This work has several potential applications such as the evaluation of geo-privacy mechanisms, the development of location-based services anticipating the next movement of a user and the design of location-aware proactive resource migration. In a nutshell, we extend a mobility model called Mobility Markov Chain (MMC) in order to incorporate the n previous visited locations and we develop a novel algorithm for next location prediction based on this mobility model that we coined as n-MMC. The evaluation of the efficiency of our algorithm on three different datasets demonstrates an accuracy for the prediction of the next location in the range of 70% to 95% as soon as n = 2.
利用移动马尔可夫链预测下一个位置
在这篇论文中,我们通过观察一个人在一段时间内的移动行为和他最近去过的地点来预测他下一个地点的问题。这项工作有几个潜在的应用,如评估地理隐私机制,开发基于位置的服务,预测用户的下一次移动,以及设计位置感知的主动资源迁移。简而言之,我们扩展了一个称为移动马尔可夫链(MMC)的移动模型,以包含n个以前访问过的位置,并基于我们称之为n-MMC的移动模型开发了一种用于下一个位置预测的新算法。我们的算法在三个不同的数据集上的效率评估表明,当n = 2时,下一个位置的预测精度在70%到95%之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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