Evaluating recommender systems: survey and framework
E Zangerle, C Bauer - ACM Computing Surveys, 2022 - dl.acm.org
The comprehensive evaluation of the performance of a recommender system is a complex
endeavor: many facets need to be considered in configuring an adequate and effective …
endeavor: many facets need to be considered in configuring an adequate and effective …
Recommendation systems: Algorithms, challenges, metrics, and business opportunities
Recommender systems are widely used to provide users with recommendations based on
their preferences. With the ever-growing volume of information online, recommender …
their preferences. With the ever-growing volume of information online, recommender …
Performance of recommender algorithms on top-n recommendation tasks
P Cremonesi, Y Koren, R Turrin - … of the fourth ACM conference on …, 2010 - dl.acm.org
In many commercial systems, the'best bet'recommendations are shown, but the predicted
rating values are not. This is usually referred to as a top-N recommendation task, where the …
rating values are not. This is usually referred to as a top-N recommendation task, where the …
[PDF][PDF] Setting goals and choosing metrics for recommender system evaluations
Recommender systems have become an important personalization technique on the web
and are widely used especially in e-commerce applications. However, operators of web …
and are widely used especially in e-commerce applications. However, operators of web …
CrossRec: Supporting software developers by recommending third-party libraries
When creating a new software system, or when evolving an existing one, developers do not
reinvent the wheel but, rather, seek available libraries that suit their purpose. In such a …
reinvent the wheel but, rather, seek available libraries that suit their purpose. In such a …
Investigating the persuasion potential of recommender systems from a quality perspective: An empirical study
P Cremonesi, F Garzotto, R Turrin - ACM Transactions on Interactive …, 2012 - dl.acm.org
Recommender Systems (RSs) help users search large amounts of digital contents and
services by allowing them to identify the items that are likely to be more attractive or useful …
services by allowing them to identify the items that are likely to be more attractive or useful …
Protomf: Prototype-based matrix factorization for effective and explainable recommendations
Recent studies show the benefits of reformulating common machine learning models
through the concept of prototypes–representatives of the underlying data, used to calculate …
through the concept of prototypes–representatives of the underlying data, used to calculate …
A recommender system for an IPTV service provider: a real large-scale production environment
R Bambini, P Cremonesi, R Turrin - Recommender systems handbook, 2010 - Springer
In this chapter we describe the integration of a recommender system into the production
environment of Fastweb, one of the largest European IP Television (IPTV) providers. The …
environment of Fastweb, one of the largest European IP Television (IPTV) providers. The …
Recommender Systems: A Review
Recommender systems are the engine of online advertising. Not only do they suggest
movies, music, or romantic partners, but they also are used to select which advertisements to …
movies, music, or romantic partners, but they also are used to select which advertisements to …
On the discriminative power of hyper-parameters in cross-validation and how to choose them
Hyper-parameters tuning is a crucial task to make a model perform at its best. However,
despite the well-established methodologies, some aspects of the tuning remain unexplored …
despite the well-established methodologies, some aspects of the tuning remain unexplored …