Matrix factorization-based methods are among the most popular methods for collaborative filtering tasks with implicit feedback. The most effective of these methods do not apply sign constraints, such as non-negativity, to their factors. Despite their simplicity, the latent factors for users and items lack interpretability, which is becoming an increasingly …

Recommender Systems support the decision making processes of customers with personalized suggestions. They are widely used and influence the daily life of almost everyone in different domains like e-commerce, social media, or entertainment. Quite often the dimension of time plays a dominant role in the generation of a relevant recommendation.

At mobile.de, Germany’s biggest car marketplace, a dedicated team of data engineers and scientists, supported by the IT project house inovex is responsible for creating intelligent data products. Driven by our company slogan “Find the car that fits your life”, we focus on personalised recommendations to address several …