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 …

Sequence-aware recommender systems

M Quadrana, P Cremonesi, D Jannach - ACM computing surveys (CSUR …, 2018 - dl.acm.org
Recommender systems are one of the most successful applications of data mining and
machine-learning technology in practice. Academic research in the field is historically often …

Fairness in recommender systems: research landscape and future directions

Y Deldjoo, D Jannach, A Bellogin, A Difonzo… - User Modeling and User …, 2024 - Springer
Recommender systems can strongly influence which information we see online, eg, on
social media, and thus impact our beliefs, decisions, and actions. At the same time, these …

News recommender systems–Survey and roads ahead

M Karimi, D Jannach, M Jugovac - Information Processing & Management, 2018 - Elsevier
More and more people read the news online, eg, by visiting the websites of their favorite
newspapers or by navigating the sites of news aggregators. However, the abundance of …

Paper recommender systems: a literature survey

J Beel, B Gipp, S Langer, C Breitinger - International Journal on Digital …, 2016 - Springer
In the last 16 years, more than 200 research articles were published about research-paper
recommender systems. We reviewed these articles and present some descriptive statistics in …

Trends in content-based recommendation: Preface to the special issue on Recommender systems based on rich item descriptions

P Lops, D Jannach, C Musto, T Bogers… - User Modeling and User …, 2019 - Springer
Automated recommendations have become a pervasive feature of our online user
experience, and due to their practical importance, recommender systems also represent an …

What recommenders recommend: an analysis of recommendation biases and possible countermeasures

D Jannach, L Lerche, I Kamehkhosh… - User Modeling and User …, 2015 - Springer
Most real-world recommender systems are deployed in a commercial context or designed to
represent a value-adding service, eg, on shopping or Social Web platforms, and typical …

A survey on popularity bias in recommender systems

A Klimashevskaia, D Jannach, M Elahi… - User Modeling and User …, 2024 - Springer
Recommender systems help people find relevant content in a personalized way. One main
promise of such systems is that they are able to increase the visibility of items in the long tail …

Recommendation quality, transparency, and website quality for trust-building in recommendation agents

M Nilashi, D Jannach, O bin Ibrahim… - Electronic Commerce …, 2016 - Elsevier
Trust is a main success factor for automated recommendation agents on e-commerce sites.
Various aspects can contribute to the development of trust toward such an agent, including …

Merging trust in collaborative filtering to alleviate data sparsity and cold start

G Guo, J Zhang, D Thalmann - Knowledge-Based Systems, 2014 - Elsevier
Providing high quality recommendations is important for e-commerce systems to assist users
in making effective selection decisions from a plethora of choices. Collaborative filtering is a …