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Itinerary recommendation based on deep learning

Itinerary recommendation is a challenging and complex field due to the lack of adequate information, incomplete knowledge about unfamiliar points of interest (POIs) and the need to account for user preferences. Visiting all attractions in a given locality is typically not possible for a given visitor due to time limitations.
openaire   +1 more source

Semantic approach to travel information search and itinerary recommendation

International Journal of Web Information Systems, 2012
PurposeThe growth of online data and services on the Web have have led to the Web become an indispensable tool for the tourist industry. It is not denied that various approaches bring benefits for visitors, in supporting their searching for tourist attractions, such as interesting places for the visit, eating or staying.
Tuan‐Dung Cao, Quang‐Minh Nguyen
openaire   +1 more source

Case-Based Recommendation for Online Judges Using Learning Itineraries

2017
Online judges are online repositories with hundreds or thousands of programming exercises or problems. They are very interesting tools for learning programming concepts, but novice users tend to feel overwhelmed by the large number of problems available.
Antonio A. Sánchez-Ruiz   +3 more
openaire   +1 more source

Smart Itinerary Recommendation Based on User-Generated GPS Trajectories

2010
Traveling to unfamiliar regions require a significant effort from novice travelers to plan where to go within a limited duration. In this paper, we propose a smart recommendation for highly efficient and balanced itineraries based on multiple user-generated GPS trajectories.
Hyoseok Yoon   +3 more
openaire   +1 more source

A Real-time Post-processing System for Itinerary Recommendation

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
Linge Jiang   +6 more
openaire   +1 more source

An integrated recommender system for multi-day tourist itinerary

Applied Soft Computing, 2023
Faezeh Ghobadi   +3 more
openaire   +1 more source

Travel recommendation and itinerary planning

AIP Conference Proceedings
Minal Barhate   +6 more
openaire   +1 more source

Personalized itinerary recommendation: Deep and collaborative learning with textual information

Expert Systems With Applications, 2020
Lu Zhang, Zhiang Wu, Jie Cao
exaly  

Crowdsourced Social Data for Recommending Tourist Itineraries

2017
Igo Ramalho Brilhante   +4 more
openaire   +1 more source

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