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  5. Customized tourist navigation in urban contexts following general trends and individual preferences

Customized tourist navigation in urban contexts following general trends and individual preferences

Author(s)
Zingoni, Andrea  
Ruko, SEDIOLA
Yeguas-Bolívar, Enrique
Alcalde-Llergo, José Manuel
Date Issued
2026
Type
article
Volume
331
Issue
133333
DOI
10.1016/j.eswa.2026.133333
Journal
EXPERT SYSTEMS WITH APPLICATIONS  
Abstract
Navigating an unfamiliar city poses significant challenges, and tourists are among the groups more likely to experience them, particularly when attempting to locate a point of interest (POI). Various factors, such as language barriers or a lack of precise information, further complicate this issue by making it difficult for visitors to explore efficiently. To address these issues, we introduce the tool “Personalized Assistant for Tourist Hints” (PATH), which is based on a methodology for estimating personalized tourist routes. PATH computes optimal paths to specified locations guided by two tailored heuristics: tourist frequency and POI preference. This integration enables efficient and personalized navigation, guiding users toward attractions that best match their preferences. We evaluated our methodology through a case study in Viterbo, Italy, using a dataset comprising over 1000 routes from 265 tourists who visited the city during different periods. To validate our approach, we tested it with 30 new tourists and collected expert assessments from 15 local specialists. User satisfaction was measured through a structured questionnaire, which revealed highly positive feedback regarding the relevance and quality of the recommended routes. Our results demonstrate PATH’s potential to enhance urban exploration by providing an adaptable and user-centric solution for tourist navigation.
Subjects

Tourism

Navigation Systems

Routing Algorithms

ReRecommendation Syst...

Urban Geography

Handle
https://dspace.unitus.it/handle/2067/70204
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Full paper (con reference).pdf

Size

3.03 MB

Format

Adobe PDF

Checksum (MD5)

6253bdaa2a11ccafba6e264fb01b946a

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