In this era of big data, the amount of video content has dramatically increased with an
exponential broadening of video streaming services. Hence, it has become very strenuous …

Owing to the enormous growth in information over the past few decades, the world has
become a global village. The recommendation system remains the most widely used type of …

As a result of a huge volume of implicit feedback such as browsing and clicks, many
researchers are involving in designing recommender systems (RSs) based on implicit …

With the emergence of e-commerce and social networking systems, the use of
recommendation systems gained popularity to predict the user ratings of an item. Since the …

Alternating Least Square (ALS) is a classic algorithm to solve matrix factorization widely
used in recommendation systems. Existing efforts focus on parallelizing ALS on multi-/many …

In recent times, Job seekers has dramatically increased. Hence, it has become very
strenuous to search for potential candidates. Recently recommendation systems have …

In e-trade websites and associated micro-blogs, users deliver online evaluations expressing
their opportunities regarding diverse gadgets. Such evaluations are commonly in the textual …

With the enlarging computation capacity of general Graphics Processing Units (GPUs),
leveraging GPUs to accelerate parallel applications has become a critical topic in academia …

En la actualidad, los sistemas de recomendación se han convertido en una herramienta
esencial en empresas que se dedican al comercio electrónico oa las redes sociales. Estos …

In the technology 4.0 era, with an increasing number of online shopping platforms opened,
increasing user interaction and enrich shopping potential to earn revenue by utilizing …