Trip destination prediction based on past GPS log using a Hidden Markov Model

被引：102

作者：

Alvarez-Garcia, J. A. ^{[2
]}

Ortega, J. A. ^{[2
]}

Gonzalez-Abril, L. ^{[1
]}

Velasco-Morente, Francisco ^{[1
]}

机构：

[1] Univ Seville, Appl Econ Dept 1, Seville 41018, Spain

[2] Univ Seville, Comp Languages & Syst Dept, E-41012 Seville, Spain

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2010年 / 37卷 / 12期

关键词：

Knowledge discovery; Machine learning; Predictive HMM; Information retrieval; PROBABILISTIC FUNCTIONS;

D O I：

10.1016/j.eswa.2010.05.070

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a system based on the generation of a Hidden Markov Model from the past GPS log and current location is presented to predict a user's destination when beginning a new trip. This approach drastically reduces the number of points supplied by the GPS device and it permits a "support-map" to be generated in which the main characteristics of the trips for each user are taken into account. Hence, in contrast with other similar approaches, total independence from a street-map database is achieved. (C) 2010 Elsevier Ltd. All rights reserved.

引用

页码：8166 / 8171

页数：6

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