Pointer-based item-to-item collaborative filtering recommendation system using a machine learning model

C Iwendi, E Ibeke, H Eggoni, S Velagala… - International Journal of …, 2022 - World Scientific
The creation of digital marketing has enabled companies to adopt personalized item
recommendations for their customers. This process keeps them ahead of the competition …

Neural TV program recommendation with label and user dual attention

F Yin, S Li, M Ji, Y Wang - Applied Intelligence, 2022 - Springer
TV program recommendation is very important for users to find interesting TV programs and
avoid confusing users with a lot of information. Currently, they are basically traditional …

Enhanced graph recommendation with heterogeneous auxiliary information

F Yin, M Ji, Y Wang, Z Yao, X Feng, S Li - Complex & Intelligent Systems, 2022 - Springer
The boom in the field of movies and TV programs, which is a kind of information overload,
may lead to poor user experience and are detrimental to the healthy development of the …

A hybrid multidimensional Recommender System for radio programs

AJ Fernández-García, R Rodriguez-Echeverria… - Expert Systems with …, 2022 - Elsevier
Abstract The rise of Recommender Systems has made their presence very common today in
many domains. An example is the domain of radio or TV broadcasting content …

IPTV channel zapping recommendation with attention mechanism

G Li, L Qiu, C Yu, H Cao, Y Liu… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Internet Protocol TV (IPTV) normally has the advantage of providing far more TV channels
than the traditional TV services, while as the other side of the coin it has the problem of …

Facing cold-start: a live TV recommender system based on neural networks

X Zhu, J Guo, S Li, T Hao - IEEE Access, 2020 - ieeexplore.ieee.org
With the increase in the number of live TV channels, audiences must spend increasing
amounts of time and energy deciding which shows to watch; this problem is called …

Neural TV program recommendation with heterogeneous attention

F Yin, M Ji, S Li, Y Wang - Knowledge and Information Systems, 2022 - Springer
TV program recommendation is very important to avoid confusing users with large amounts
of information. The existing methods are mainly based on collaborative filtering to utilize the …

A novel method for IPTV customer behavior analysis using time series

T Hlupić, D Oreščanin, M Baranović - IEEE Access, 2022 - ieeexplore.ieee.org
Internet Protocol Television (IPTV) has had a significant impact on live TV content
consumption in the past decade, as improvements in the broadband speed have allowed …

Giving and following recommendations on video-on-demand services

J Gutzeit, I Dorsch, W Stock - 2022 - scholarspace.manoa.hawaii.edu
This is an empirical paper about giving, receiving and following recommendations on Video-
on-Demand (VoD) services, including results on gender-specific differences. Based upon a …

Exploring Auxiliary Information Integration for Neural TV Program Recommendation

Y Wu, R Fu, T Xing, F Yin - 2024 3rd International Conference …, 2024 - ieeexplore.ieee.org
TV program recommendations enable users to discover programs of interest within the large
amount of information available. Most of the existing methods use userprogram interaction …