Recommender systems: Techniques, applications, and challenges
Recommender systems (RSs) are software tools and techniques that provide suggestions
for items that are most likely of interest to a particular user. In this introductory chapter, we …
for items that are most likely of interest to a particular user. In this introductory chapter, we …
[HTML][HTML] How can we create a recommender system for tourism? A location centric spatial binning-based methodology using social networks
Point of Interest (POI) recommendation is an important Location-Based Social Network
(LBSN) task that has become a hotspot in the past decade. It aims to exploit the user's …
(LBSN) task that has become a hotspot in the past decade. It aims to exploit the user's …
Modeling sustainable city trips: integrating emissions, popularity, and seasonality into tourism recommender systems
A Banerjee, T Mahmudov, E Adler, FN Aisyah… - … Technology & Tourism, 2025 - Springer
Tourism affects not only the tourism industry but also society and stakeholders such as the
environment, local businesses, and residents. Tourism recommender systems (TRS) can be …
environment, local businesses, and residents. Tourism recommender systems (TRS) can be …
Sco** out urban areas of tourist interest though geolocated social media data: Bucharest as a case study
Social media data has frequently sourced research on topics such as traveller planning or
the factors that influence travel decisions. The literature on the location of tourist activities …
the factors that influence travel decisions. The literature on the location of tourist activities …
Recommender systems in tourism
F Ricci - Handbook of e-Tourism, 2022 - Springer
Recommender systems (RSs) are information search and filtering tools that provide
suggestions for items to be of use to a user. They are now common in many Internet …
suggestions for items to be of use to a user. They are now common in many Internet …
Popularity, novelty and relevance in point of interest recommendation: an experimental analysis
Abstract Recommender Systems (RSs) are often assessed in off-line settings by measuring
the system precision in predicting the observed user's ratings or choices. But, when a …
the system precision in predicting the observed user's ratings or choices. But, when a …
Studying spatial and temporal visitation patterns of points of interest using SafeGraph data in Florida
L Juhász, HH Hochmair - 2020 - digitalcommons.fiu.edu
SafeGraph is a commercial provider of massive Point of Interest (POI) data, including
visitation patterns in North America. Although the data source does not share specific travel …
visitation patterns in North America. Although the data source does not share specific travel …
Identification of mobility patterns of clusters of city visitors: An application of artificial intelligence techniques to social media data
In order to enhance tourists' experiences, Destination Management Organizations need to
know who their tourists are, their travel preferences, and their flows around the destination …
know who their tourists are, their travel preferences, and their flows around the destination …
Recommendation system algorithms on location-based social networks: Comparative study
Currently, social networks allow individuals from all over the world to share ideas, activities,
events, and interests over the Internet. Using location-based social networks (LBSNs), users …
events, and interests over the Internet. Using location-based social networks (LBSNs), users …
[PDF][PDF] Designing a Conversational Travel Recommender System Based on Data-Driven Destination Characterization.
Recommending complex, intangible items in a domain with high consequences, such as
destinations for traveling, requires additional care when deriving and confronting the users …
destinations for traveling, requires additional care when deriving and confronting the users …