Discrete Listwise Content-aware Recommendation

F Luo, J Wu, T Wang - ACM Transactions on Knowledge Discovery from …, 2023 - dl.acm.org
To perform online inference efficiently, hashing techniques, devoted to encoding model
parameters as binary codes, play a key role in reducing the computational cost of content …

[PDF][PDF] Combining Unstructured Content and Knowledge Graphs into Recommendation Datasets.

W Lin, L Shou, M Gong, J Pei, Z Wang, B Byrne… - KaRS@ RecSys, 2022 - ceur-ws.org
Popular book and movie recommendation datasets can be associated with Knowledge
Graphs (KG) that enable the development of KG-based recommender systems. However …

Designing a Movie Recommendation System Through a Transformer-Based Embeddings Space

JO López - 2024 IEEE Colombian Conference on …, 2024 - ieeexplore.ieee.org
Artificial intelligence has found a critical use in recommender systems, especially in the film
industry. Recommender systems have attracted a lot of attention due to their capacity to …

Augmenting Multi-modal Question Answering Systems with Retrieval Methods

W Lin - 2024 - repository.cam.ac.uk
The quest to develop artificial intelligence systems capable of handling intricate tasks has
propelled the prominence of deep learning, particularly since 2016, when neural network …

AI Assisting Individuals as Team Members

DC Gibson, D Ifenthaler - Computational Learning Theories: Models for …, 2024 - Springer
This chapter provides guiding ideas, based on the micro and meso frameworks developed
thus far, for the development of AI applications that enhance a team's or organization's …

[PDF][PDF] CUSTOMIZING COMMONALITIES GROUNDED INTERNET SERVICE RECOMMENDER SYSTEM USING COLLABORATIVE FILTERING

K SELVARANI, A ANNADHASON - Journal of Theoretical and Applied …, 2023 - jatit.org
In the realm of the Internet, Recommender Systems (RS) play a pivotal role in enhancing
data retrieval techniques, thereby optimizing the utilization of online data. These systems …