Our paper on Early Destination Prediction with Spatio-temporal User Behavior Patterns has been published in Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT).

We propose a new probabilistic destination prediction model based on two conventional models,
trajectory tracking that narrows down the candidates with respect to the trip progress, and Next Place Prediction (NPP) that infers the future location of a user from user habits.

The advantage of our model is that it drastically narrows down the destination candidates efficiently at the early stage of a trip, owing to the staying information derived from the NPP approach.

The proposed method provides improved performance compared to conventional approaches based on the experimental results using the GPS logs of 1,646 actual users from the commercial services.

The paper is publicly available, i.e. open access in the following url, please check our paper.

Ryo Imai and Kota Tsubouchi and Tatsuya Konishi and Masamichi Shimosaka
Early Destination Prediction with Spatio-temporal User Behavior Patterns.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 1, No. 4, pp. 142:1–142:19, 2017.

Project page is here.