A framework of route recommendation system for sightseeing from subjective and objective evaluation of tourism data

This paper proposes a framework to recommend personal sightseeing route as well as to objectively obtain the tourist's utility to sightseeing plans and sightseeing spots from subjective comparison. The subjective comparison is qualitatively performed using a scale of measurement such as Likert scale, and the mathematical programming problem including this comparison as constraints is introduced. In the case of route planning, traveling and sightseeing times are randomly changed dependent on current traffic and congestion conditions, and hence, Time-Expanded Network (TEN) to represent these traffic conditions in the underlying static network with each discrete time step is introduced. In addition, the network optimization problem is introduced to obtain the personal appropriate sightseeing route. This problem is formulated as a nonlinear and discrete optimization problem, and it is hard to solve it directly and efficiently. Therefore, an efficient algorithm is also developed based on dynamic programming and transformation of the main problem into the recursive equation.