Towards Next Generation Touring: Personalized Group Tours. Lim, K. H., Chan, J., Leckie, C., & Karunasekera, S. In
Towards Next Generation Touring: Personalized Group Tours [link]Paper  abstract   bibtex   
Recommending and planning tour itineraries are challenging and time-consuming for tourists, hence they may seek tour operators for help. Traditionally tour operators have offered standard tour packages of popular locations, but these packages may not cater to tourist's interests. In addition, tourists may want to travel in a group, e.g., extended family, and want an operator to help them. In this paper, we introduce the novel problem of group tour recommendation (GroupTourRec), which involves many challenges: forming tour groups whose members have similar interests; recommending Points-of-Interests (POI) that form the tour itinerary and cater for the group's interests; and assigning guides to lead these tours. For each challenge, we propose solutions involving: clustering for tourist groupings; optimizing a variant of the Orienteering problem for POI recommendations; and integer programming for tour guide assignments. Using a Flickr dataset of seven cities, we compare our proposed approaches against various baselines and observe significant improvements in terms of interest similarity, total/maximum/minimum tour interests and total tour guide expertise.
@inproceedings {icaps16-72,
    track    = {​​​Applications Track},
    title    = {Towards Next Generation Touring: Personalized Group Tours},
    url      = {http://www.aaai.org/ocs/index.php/ICAPS/ICAPS16/paper/view/12803},
    author   = {Kwan Hui Lim and  Jeffrey Chan and  Christopher Leckie and  Shanika Karunasekera},
    abstract = {Recommending and planning tour itineraries are challenging and time-consuming for tourists, hence they may seek tour operators for help. Traditionally tour operators have offered standard tour packages of popular locations, but these packages may not cater to tourist's interests.  In addition, tourists may want to travel in a group, e.g., extended family, and want an operator to help them.  In this paper, we introduce the novel problem of group tour recommendation (GroupTourRec), which involves many challenges: forming tour groups whose members have similar interests; recommending Points-of-Interests (POI) that form the tour itinerary and cater for the group's interests; and assigning guides to lead these tours. For each challenge, we propose solutions involving: clustering for tourist groupings; optimizing a variant of the Orienteering problem for POI recommendations; and integer programming for tour guide assignments. Using a Flickr dataset of seven cities, we compare our proposed approaches against various baselines and observe significant improvements in terms of interest similarity, total/maximum/minimum tour interests and total tour guide expertise.},
    keywords = {Evaluation; testing; and validation of P&S applications,Description and modeling of novel application domains,Integration of multiple P&S techniques; or of P&S techniques with techniques from other areas}
}
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