Latent Factors

Item features play an important role in movie recommender systems, where recommendations can be generated by using explicit or implicit preferences of users on attributes such as genres. Traditionally, movie features are human-generated, either editorially or by leveraging the wisdom of the crowd.
In this short paper, we present a recommender system for movies based of Factorization Machines that makes use of the low-level visual features extracted automatically from movies as side information. Low-level visual features – such as lighting, colors and motion – represent the design aspects of a movie and characterize its aesthetic and style.
Our experiments on a dataset of more than 13K movies show that recommendations based on low-level visual features provides almost 10 times better accuracy in comparison to genre based recommendations, in terms of various evaluation metrics.

Performance of students in mathematics has been the focus of so many studies in education. Its fluctuating record in national and international arena calls the attention of every researcher in mathematics to refocus their attention to identifying latent that possibly explain this performance. This current study believes that students' performance in mathematics can be predicted by some latent variables. These sets of possibly correlated manifest variables are combined to form latent variables that are transformed into a set of values of linearly uncorrelated variables called principal components. These components would then become the input to the model predicting secondary students' performance in mathematics. Moreover, Regression Analysis was employed to develop a model predicting secondary students' performance in mathematics. The study revealed that peer relation index, luxury index, and personal characteristics were significant predictors of Mathematics performance among secondary students. More so, it supports social-cognitive theory and strengthens its foundation that cognition and social relation greatly determines the behavior and performance of social individuals.