171 citations · 323 across the 14 of their papers we have counts for
6 papers · 1 filter
Ethical AI prompt recommendations in large language models using collaborative filtering
Jordan Nelson, Almas Baimagambetov, Konstantinos Avgerinakis +1
As large language models (LLMs) shape AI development, ensuring ethical prompt recommendations is crucial. LLMs offer innovation but risk bias, fairness issues, and accountability c…
Mobile recommender systems: Identifying the major concepts
Elias Pimenidis, Nikolaos Polatidis, Haralambos Mouratidis
This paper identifies the factors that have an impact on mobile recommender systems. Recommender systems have become a technology that has been widely used by various online applic…
From product recommendation to cyber-attack prediction: Generating attack graphs and predicting future attacks
Nikolaos Polatidis, Elias Pimenidis, Michalis Pavlidis +2
Modern information society depends on reliable functionality of information systems infrastructure, while at the same time the number of cyber-attacks has been increasing over the…
A multi-level collaborative filtering method that improves recommendations
Nikolaos Polatidis, Christos K. Georgiadis
Collaborative filtering is one of the most used approaches for providing recommendations in various online environments. Even though collaborative recommendation methods have been…
A dynamic multi-level collaborative filtering method for improved recommendations
Nikolaos Polatidis, Christos K. Georgiadis
One of the most used approaches for providing recommendations in various online environments such as e-commerce is collaborative filtering. Although, this is a simple method for re…
Mobile recommender systems: An overview of technologies and challenges
Nikolaos Polatidis, Christos K. Georgiadis
The use of mobile devices in combination with the rapid growth of the internet has generated an information overload problem. Recommender systems is a necessity to decide which of…