PARecommender: A Pattern-Based System for Route Recommendation

Feiyi Tang, Jia Zhu, Yang Cao, Sanli Ma, Yulong Chen, Jing He, Changqin Huang, Gansen Zhao, Yong Tang

Abstract: Widely adoption of GPS-enabled devices generates massive trajectory data every minute. The trajectory data can generate meaningful traffic patterns. In this demo, we present a system called PARecommender, which predicts traffic conditions and provides route recommendation based on generated traffic patterns. We first introduce the technical details of PARecommender, and then show several real cases that how PARecommender works.