|
|
|
|
|
Deepanjal Shrestha, Tan Wenan, Deepmala Shrestha, Neesha Rajkarnikar and Seung-Ryul Jeong
This study introduces a data-driven and machine-learning approach to design a personalized tourist recommendation system for Nepal. It examines key tourist attributes, such as demographics, behaviors, preferences, and satisfaction, to develop four sub-mo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Lamyae El Youbi El Idrissi, Ismail Akharraz and Abdelaziz Ahaitouf
|
|
|
|
|
|
|
|
|
|
|
Jiaxu Zhao, Binting Su, Xuli Rao and Zhide Chen
In this paper, we build a recommender system for a new study area: social commerce, which combines rich information about social network users and products on an e-commerce platform. The idea behind this recommender system is that a social network contai...
ver más
|
|
|
|
|
|
|
|
|
|
|
Christos Troussas, Akrivi Krouska, Antonios Koliarakis and Cleo Sgouropoulou
Recommender systems are widely used in various fields, such as e-commerce, entertainment, and education, to provide personalized recommendations to users based on their preferences and/or behavior. ?his paper presents a novel approach to providing custom...
ver más
|
|
|
|
|
|
|
|
|
|
|
Leyla Gamidullaeva, Alexey Finogeev, Mikhail Kataev and Larisa Bulysheva
Despite of tourism infrastructure and software, the development of tourism is hampered due to the lack of information support, which encapsulates various aspects of travel implementation. This paper highlights a demand for integrating various approaches ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Bin Cheng, Ping Chen, Xin Zhang, Keyu Fang, Xiaoli Qin and Wei Liu
With the rapid development of ubiquitous data collection and data analysis, data privacy in a recommended system is facing more and more challenges. Differential privacy technology can provide strict privacy protection while reducing the risk of privacy ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Aleksandar Ivanovski, Milos Jovanovik, Riste Stojanov and Dimitar Trajanov
In this work, we present a state-of-the-art solution for automatic playlist continuation through a knowledge graph-based recommender system. By integrating representational learning with graph neural networks and fusing multiple data streams, the system ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Manolis Remountakis, Konstantinos Kotis, Babis Kourtzis and George E. Tsekouras
Recommender systems have become indispensable tools in the hotel hospitality industry, enabling personalized and tailored experiences for guests. Recent advancements in large language models (LLMs), such as ChatGPT, and persuasive technologies have opene...
ver más
|
|
|
|
|
|
|
|
|
|
|
Hyeon Jo, Jong-hyun Hong and Joon Yeon Choeh
In recent years, virtual online communities have experienced rapid growth. These communities enable individuals to share and manage images or websites by employing tags. A collaborative tagging system (CTS) facilitates the process by which internet users...
ver más
|
|
|
|
|
|
|
|
|
|
|
Georgios Chalkiadakis, Ioannis Ziogas, Michail Koutsmanis, Errikos Streviniotis, Costas Panagiotakis and Harris Papadakis
In this paper, we develop a novel hybrid recommender system for the tourism domain, which combines (a) a Bayesian preferences elicitation component which operates by asking the user to rate generic images (corresponding to generic types of POIs) in order...
ver más
|
|
|
|
|
|