Itinerary recommendations dataset

Citation Author(s):
Federica
Cena
University of Turin
Luca
Console
University of Turin
Marta
Micheli
University of Turin
Fabiana
Vernero
University of Turin
Submitted by:
Fabiana Vernero
Last updated:
Tue, 05/07/2024 - 10:57
DOI:
10.21227/zk2x-pk70
Data Format:
*.csv ; *.xlsx
License:
Creative Commons Attribution
113 Views
Categories:
Artificial Intelligence
Other
Keywords:
Recommender System, user experience
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Abstract 

The dataset presents user evaluations for itinerary recommendations generated with three algorithms, PP, PP+TS and PP+TP.
Users evaluated recommendations according to five properties:

  • overall evaluation (i.e., how good the recommended itinerary is overall),
  • acceptance (i.e., how likely it is that the recommendation is actually accepted)
  • organisation (i.e., how good the recommended itinerary is considering transfer times, number of PoIs, heterogeneity among PoIs, busy hours avoidance),
  • PoIs (i.e., how good the recommended itinerary is as for the choice of PoIs to visit)
  • free time (i.e., how good the recommended itinerary is as for the quantity of free time).

In the dataset, each row corresponds to a user. There are 124 users.

Instructions: 

Each row corresponds to a user.

Columns correspond to properties:
UID_user - anonmous user ID
PP.overall - overall evaluation (i.e., how good the recommended itinerary is overall) for PP algorithm
PP.acceptance - acceptance (i.e., how likely it is that the recommendation is actually accepted) for PP algorithm
PP.organization- organisation (i.e., how good the recommended itinerary is considering transfer times, number of PoIs, heterogeneity among PoIs, busy hours avoidance) for PP algorithm
PP.POI - PoIs (i.e., how good the recommended itinerary is as for the choice of PoIs to visit) for PP algorithm
PP.free_time - free time (i.e., how good the recommended itinerary is as for the quantity of free time) for PP algorithm
PP+TS.overall - overall evaluation (i.e., how good the recommended itinerary is overall) for PP+TS algorithm
PP+TS.acceptance - acceptance (i.e., how likely it is that the recommendation is actually accepted) for PP+TS algorithm
PP+TS.organization - organisation (i.e., how good the recommended itinerary is considering transfer times, number of PoIs, heterogeneity among PoIs, busy hours avoidance) for PP+TS algorithm
PP+TS.POI - PoIs (i.e., how good the recommended itinerary is as for the choice of PoIs to visit) for PP+TS algorithm
PP+TS.free_time - free time (i.e., how good the recommended itinerary is as for the quantity of free time) for PP+TS algorithm
PP+TP.overall - overall evaluation (i.e., how good the recommended itinerary is overall) for PP+TP algorithm
PP+TP.acceptance - acceptance (i.e., how likely it is that the recommendation is actually accepted) for PP+TP algorithm
PP+TP.organization - organisation (i.e., how good the recommended itinerary is considering transfer times, number of PoIs, heterogeneity among PoIs, busy hours avoidance) for PP+TP algorithm
PP+TP.POI - PoIs (i.e., how good the recommended itinerary is as for the choice of PoIs to visit) for PP+TP algorithm
PP+TP.free_time - free time (i.e., how good the recommended itinerary is as for the quantity of free time) for PP+TP algorithm

Values range fro 1 (minimum) to 5 (maximum)

 

 

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