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In recent years, there has been a growing interest in travel applicationsthat provide on-site personalized tourist spot recommendations. While generallyhelpful, most available options offer choices based solely on staticinformation on places of interest without consideration of such dynamic factorsas weather, time of day, and congestion, and with a focus on helping thetourist decide what single spot to visit next. Such limitations may preventvisitors from optimizing the use of their limited resources (i.e., time andmoney). Some existing studies allow users to calculate a semi-optimal tourvisiting multiple spots in advance, but their on-site use is difficult due tothe large computation time, no consideration of dynamic factors, etc. To dealwith this situation, we formulate a tour score approach with three components:static tourist information on the next spot to visit, dynamic touristinformation on the next spot to visit, and an aggregate measure of satisfactionassociated with visiting the next spot and the set of subsequent spots to bevisited. Determining the tour route that produces the best overall tour scoreis an NP-hard problem for which we propose three algorithms on the greedymethod. To validate the usefulness of the proposed approach, we applied thethree algorithms to 20 points of interest in Higashiyama, Kyoto, Japan, andconfirmed that the output solution was superior to the model route for Kyoto,with computation times of the three algorithms of $1.9\pm0.1$, $2.0\pm0.1$, and$27.0\pm1.8$ s.

Timeliness-aware On-site Planning Method for Tour Navigation