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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, 2012PurposeThe 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
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Case-Based Recommendation for Online Judges Using Learning Itineraries
2017Online 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
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Smart Itinerary Recommendation Based on User-Generated GPS Trajectories
2010Traveling 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
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A Real-time Post-processing System for Itinerary Recommendation
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022Linge Jiang +6 more
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An integrated recommender system for multi-day tourist itinerary
Applied Soft Computing, 2023Faezeh Ghobadi +3 more
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Travel recommendation and itinerary planning
AIP Conference ProceedingsMinal Barhate +6 more
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MultiCity: A Personalized Multi-itinerary City Recommendation Engine
2022Joy Lal Sarkar, Abhishek Majumder
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Personalized itinerary recommendation: Deep and collaborative learning with textual information
Expert Systems With Applications, 2020Lu Zhang, Zhiang Wu, Jie Cao
exaly
Crowdsourced Social Data for Recommending Tourist Itineraries
2017Igo Ramalho Brilhante +4 more
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