Predicting Routes and Destinations of Urban Trips using PPM Method - N. Neto, Francisco; Baptista, Cláudio; Campelo, Cláudio (Anais do Simpósio Brasileiro de Computação Ubíqua e Pervasiva (SBCUP); 2015: Anais do VII Simpósio Brasileiro de Computação Ubíqua e Pervasiva, 2015)
Information about destination and route that a person will take is important for various purposes, such as to prevent a user going through a congested route. However, an information system where users must explicitly input their intended destination seems not be useful for daily routines. Ideally, the system should be able to predict the destination and the route to be taken by a vehicle as soon as it starts to move. This paper presents a new technique to predict route and destination, based on Prediction by Partial Matching (PPM) compression method. By considering two important contextual information (day of week and time of departure), the results obtained by our approach were encouraging, reaching around 92% of accuracy rate.