A literature review of recommender systems in the television domain

D Véras, T Prota, A Bispo, R Prudêncio… - Expert Systems with …, 2015 - Elsevier
Abstract Recommender Systems (RSs) are software tools and techniques providing
suggestions of relevant items to users. These systems have received increasing attention …

Semantics-aware content-based recommender systems

M De Gemmis, P Lops, C Musto, F Narducci… - Recommender systems …, 2015 - Springer
Content-based recommender systems (CBRSs) rely on item and user descriptions (content)
to build item representations and user profiles that can be effectively exploited to suggest …

Content-based video recommendation system based on stylistic visual features

Y Deldjoo, M Elahi, P Cremonesi, F Garzotto… - Journal on Data …, 2016 - Springer
This paper investigates the use of automatically extracted visual features of videos in the
context of recommender systems and brings some novel contributions in the domain of …

Using visual features based on MPEG-7 and deep learning for movie recommendation

Y Deldjoo, M Elahi, M Quadrana… - International journal of …, 2018 - Springer
Item features play an important role in movie recommender systems, where
recommendations can be generated by using explicit or implicit preferences of users on …

Linked open data-based explanations for transparent recommender systems

C Musto, F Narducci, P Lops, M De Gemmis… - International Journal of …, 2019 - Elsevier
In this article we propose a framework that generates natural language explanations
supporting the suggestions generated by a recommendation algorithm. The cornerstone of …

[图书][B] Social data analytics

A Beheshti, S Ghodratnama, M Elahi, H Farhood - 2022 - taylorfrancis.com
This book is an introduction to social data analytics along with its challenges and
opportunities in the age of Big Data and Artificial Intelligence. It focuses primarily on …

A deep architecture for content-based recommendations exploiting recurrent neural networks

A Suglia, C Greco, C Musto, M De Gemmis… - Proceedings of the 25th …, 2017 - dl.acm.org
In this paper we investigate the effectiveness of Recurrent Neural Networks (RNNs) in a top-
N content-based recommendation scenario. Specifically, we propose a deep architecture …

Knowledge-aware recommendations based on neuro-symbolic graph embeddings and first-order logical rules

G Spillo, C Musto, M De Gemmis, P Lops… - Proceedings of the 16th …, 2022 - dl.acm.org
In this paper, we present a knowledge-aware recommendation framework based on neuro-
symbolic graph embeddings that encode first-order logical (FOL) rules. In particular, our …

Deep content-based recommender systems exploiting recurrent neural networks and linked open data

C Musto, T Franza, G Semeraro, M De Gemmis… - Adjunct Publication of …, 2018 - dl.acm.org
In this paper we present a deep content-based recommender system (DeepCBRS) that
exploits Bidirectional Recurrent Neural Networks (BRNNs) to learn an effective …

Concept-based item representations for a cross-lingual content-based recommendation process

F Narducci, P Basile, C Musto, P Lops, A Caputo… - Information …, 2016 - Elsevier
The growth of the Web is the most influential factor that contributes to the increasing
importance of text retrieval and filtering systems. On one hand, the Web is becoming more …