Social network data to alleviate cold-start in recommender system: A systematic review

LAG Camacho, SN Alves-Souza - Information Processing & Management, 2018 - Elsevier
Recommender Systems are currently highly relevant for helping users deal with the
information overload they suffer from the large volume of data on the web, and automatically …

A systematic review of recommender systems and their applications in cybersecurity

A Pawlicka, M Pawlicki, R Kozik, RS Choraś - Sensors, 2021 - mdpi.com
This paper discusses the valuable role recommender systems may play in cybersecurity.
First, a comprehensive presentation of recommender system types is presented, as well as …

Recommender systems challenges and solutions survey

MH Mohamed, MH Khafagy… - … on innovative trends in …, 2019 - ieeexplore.ieee.org
Today's Recommender system is a relatively new area of research in machine learning. The
recommender system's main idea is to build relationship between the products, users and …

A new similarity measure for collaborative filtering based recommender systems

A Gazdar, L Hidri - Knowledge-Based Systems, 2020 - Elsevier
The objective of a recommender system is to provide customers with personalized
recommendations while selecting an item among a set of products (movies, books, etc.). The …

An enhanced recommender system based on heterogeneous graph link prediction

Y Afoudi, M Lazaar, S Hmaidi - Engineering Applications of Artificial …, 2023 - Elsevier
Graph-based data has gained popularity in various applications, including social networks,
recommendation systems, and knowledge graphs. Detecting missing links between nodes is …

A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits

L Leqi, G Zhou, F Kilinc-Karzan, Z Lipton… - Proceedings of the …, 2023 - dl.acm.org
Personalized recommender systems suffuse modern life, shaping what media we read and
what products we consume. Algorithms powering such systems tend to consist of supervised …

PDMFRec: a decentralised matrix factorisation with tunable user-centric privacy

E Duriakova, EZ Tragos, B Smyth, N Hurley… - Proceedings of the 13th …, 2019 - dl.acm.org
Conventional approaches to matrix factorisation (MF) typically rely on a centralised
collection of user data for building a MF model. This approach introduces an increased risk …

Pattern-based hybrid book recommendation system using semantic relationships

F Wayesa, M Leranso, G Asefa, A Kedir - Scientific Reports, 2023 - nature.com
In the fields of machine learning and artificial intelligence, recommendation systems (RS) or
recommended engines are commonly used. In today's world, recommendation systems …

Sentiment analysis of social network data for cold-start relief in recommender systems

FG Contratres, SN Alves-Souza, LVL Filgueiras… - Trends and Advances in …, 2018 - Springer
Recommender systems have been used in e-commerce to increase conversion due to
matching product offer and consumer preferences. Cold-start is the situation of a new user …

OCC: a hybrid multiprocessing computing service decision making using ontology system

A Tiwari, RM Sharma - International Journal of Web-Based Learning …, 2021 - igi-global.com
In the recent trends, cloud computing service users agreed on the concept of pay and use
model by accessing all the best services provided by the providers. The major problem here …