|
|
|
|
|
Hajar Majjate, Youssra Bellarhmouch, Adil Jeghal, Ali Yahyaouy, Hamid Tairi and Khalid Alaoui Zidani
Over the past few decades, the education sector has achieved impressive advancements by incorporating Artificial Intelligence (AI) into the educational environment. Nevertheless, specific educational processes, particularly educational counseling, still ...
ver más
|
|
|
|
|
|
|
|
|
|
|
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
|
|
|
|
|
|
|
|
|
|
|
Wenkai Ni, Yanhui Du, Xingbang Ma and Haibin Lv
One of the five types of Internet information service recommendation technologies is the personalized recommendation algorithm, and knowledge graphs are frequently used in these algorithms. RippleNet is a personalized recommendation model based on knowle...
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
|
|
|
|
|
|
|
|
|
|
|
Marwa Abdelreheim, Taysir Hassan A. Soliman and Friederike Klan
The profusion of existing ontologies in different domains has made reusing ontologies a best practice when developing new ontologies. The ontology reuse process reduces the expensive cost of developing a new ontology, in terms of time and effort, and sup...
ver más
|
|
|
|
|
|
|
|
|
|
|
Chin-Yi Chen and Jih-Jeng Huang
Traditional movie recommendation systems are increasingly falling short in the contemporary landscape of abundant information and evolving user behaviors. This study introduced the temporal knowledge graph recommender system (TKGRS), a ground-breaking al...
ver más
|
|
|
|
|
|
|
|
|
|
|
Christos Troussas, Akrivi Krouska, Panagiota Tselenti, Dimitrios K. Kardaras and Stavroula Barbounaki
The extensive pool of content within educational software platforms can often overwhelm learners, leaving them uncertain about what materials to engage with. In this context, recommender systems offer significant support by customizing the content delive...
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
|
|
|
|
|
|
|
|
|
|
|
Ikram Karabila, Nossayba Darraz, Anas El-Ansari, Nabil Alami and Mostafa El Mallahi
Recommendation systems (RSs) are widely used in e-commerce to improve conversion rates by aligning product offerings with customer preferences and interests. While traditional RSs rely solely on numerical ratings to generate recommendations, these rating...
ver más
|
|
|
|
|
|
|
|
|
|
|
Syed Raza Bashir, Shaina Raza and Vojislav B. Misic
Recommending points of interest (POI) is a challenging task that requires extracting comprehensive location data from location-based social media platforms. To provide effective location-based recommendations, it is important to analyze users? historical...
ver más
|
|
|
|
|
|