Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.eswa.2010.05.070 | Expert Syst. Appl. |
Keywords | Field | DocType |
new trip,information retrieval,predictive hmm,gps device,similar approach,trip destination prediction,knowledge discovery,total independence,past gps log,main characteristic,machine learning,hidden markov model,current location,street-map database | Data mining,Markov model,Computer science,Artificial intelligence,Knowledge extraction,Global Positioning System,TRIPS architecture,Hidden Markov model,Machine learning,Hidden semi-Markov model | Journal |
Volume | Issue | ISSN |
37 | 12 | Expert Systems With Applications |
Citations | PageRank | References |
24 | 0.84 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. A. Alvarez-Garcia | 1 | 31 | 1.30 |
| J. A. Ortega | 2 | 99 | 7.03 |
| L. Gonzalez-Abril | 3 | 153 | 8.48 |
| F. Velasco | 4 | 106 | 5.83 |