Mining Popular Paths in a Transportation Database System with Privacy Protection

Abstract

This paper proposes an algorithm to identify popular paths in a transportation system, while the privacy of drivers is preserved. A popular path is one of the most frequently used routes between any two points in a road map. In order to identify popular paths with privacy protection, the algorithm figures out what information is useless for identifying popular paths, and this information is not revealed to the data mining system so that privacy is preserved. In addition, the system does not record the identifications of the vehicles. Moreover, in the mining process, the database does not contain complete path information. The experimental results verify the correctness of the proposed algorithm and show that the proposed algorithm is scalable.