Multi-branch LSTM encoded latent features with CNN-LSTM for Youtube popularity prediction
Sign Up to like & getrecommendations! Published in 2025 at "Scientific Reports"
DOI: 10.1038/s41598-025-86785-3
Abstract: As digital media grows, there is an increasing demand for engaging content that can captivate audiences. Along with that, the monetary conversion of those engaging videos is also increased. This leads to the way for… read more here.
Keywords: popularity prediction; latent features; lstm; multi branch ... See more keywords
Unlocking latent features of users and items: empowering multi-modal recommendation systems
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DOI: 10.1038/s41598-025-95872-4
Abstract: Multimedia recommendation has emerged as a pivotal area in contemporary research, propelled by the exponential growth of digital media consumption. In recent years, the proliferation of multimedia content across diverse platforms has necessitated sophisticated recommendation… read more here.
Keywords: unlocking latent; recommendation systems; features users; recommendation ... See more keywords
Deep clustering of protein folding simulations
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DOI: 10.1186/s12859-018-2507-5
Abstract: BackgroundWe examine the problem of clustering biomolecular simulations using deep learning techniques. Since biomolecular simulation datasets are inherently high dimensional, it is often necessary to build low dimensional representations that can be used to extract… read more here.
Keywords: protein; latent features; protein folding; cvae model ... See more keywords
Disentangling genotype and environment specific latent features for improved trait prediction using a compositional autoencoder
Sign Up to like & getrecommendations! Published in 2024 at "Frontiers in Plant Science"
DOI: 10.3389/fpls.2024.1476070
Abstract: In plant breeding and genetics, predictive models traditionally rely on compact representations of high-dimensional data, often using methods like Principal Component Analysis (PCA) and, more recently, Autoencoders (AE). However, these methods do not separate genotype-specific… read more here.
Keywords: autoencoder; genotype; latent features; environment specific ... See more keywords
Matrix Factorization Recommendation Algorithm Based on Attention Interaction
Sign Up to like & getrecommendations! Published in 2024 at "Symmetry"
DOI: 10.3390/sym16030267
Abstract: Recommender systems are widely used in e-commerce, movies, music, social media, and other fields because of their personalized recommendation functions. The recommendation algorithm is used to capture user preferences, item characteristics, and the items that… read more here.
Keywords: attention; algorithm; model; recommendation ... See more keywords