Personalized one-day travel with multi-nearby-landmark recommendation

Siya Bao, Masao Yanagisawa, Nozomu Togawa · 2017

Travel route recommendation can strongly influence users' satisfaction and the success of touristic businesses. This paper proposes a personalized travel recommendation algorithm with time planning. We use landmark categorization and region clustering to obtain effective elements. Then we build a travel map to generate all possible travel routes. Our proposed algorithm has higher precision in landmark recommendation and time planning than those in previous algorithms.

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