research
∙
07/19/2023
Reproducibility in Machine Learning-Driven Research
Research is facing a reproducibility crisis, in which the results and fi...
share
research
∙
03/01/2023
A Study on Accuracy, Miscalibration, and Popularity Bias in Recommendations
Recent research has suggested different metrics to measure the inconsist...
research
∙
02/07/2023
A conceptual model for leaving the data-centric approach in machine learning
For a long time, machine learning (ML) has been seen as the abstract pro...
research
∙
01/03/2023
Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings
In this work, we tackle the problem of adapting a real-time recommender ...
research
∙
10/21/2022
Towards Employing Recommender Systems for Supporting Data and Algorithm Sharing
Data and algorithm sharing is an imperative part of data and AI-driven e...
research
∙
08/17/2022
Long-term dynamics of fairness: understanding the impact of data-driven targeted help on job seekers
The use of data-driven decision support by public agencies is becoming m...
research
∙
06/23/2022
ReuseKNN: Neighborhood Reuse for Privacy-Aware Recommendations
User-based KNN recommender systems (UserKNN) utilize the rating data of ...
research
∙
03/02/2022
Recommendations in a Multi-Domain Setting: Adapting for Customization, Scalability and Real-Time Performance
In this industry talk at ECIR'2022, we illustrate how to build a modern ...
research
∙
03/01/2022
Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems
Multimedia recommender systems suggest media items, e.g., songs, (digita...
research
∙
11/29/2021
What Drives Readership? An Online Study on User Interface Types and Popularity Bias Mitigation in News Article Recommendations
Personalized news recommender systems support readers in finding the rig...
research
∙
09/14/2021
Position Paper on Simulating Privacy Dynamics in Recommender Systems
In this position paper, we discuss the merits of simulating privacy dyna...
research
∙
08/16/2021
Analyzing Item Popularity Bias of Music Recommender Systems: Are Different Genders Equally Affected?
Several studies have identified discrepancies between the popularity of ...
research
∙
02/24/2021
Support the Underground: Characteristics of Beyond-Mainstream Music Listeners
Music recommender systems have become an integral part of music streamin...
research
∙
01/18/2021
Robustness of Meta Matrix Factorization Against Strict Privacy Constraints
In this paper, we explore the reproducibility of MetaMF, a meta matrix f...
research
∙
09/11/2020
Listener Modeling and Context-aware Music Recommendation Based on Country Archetypes
Music preferences are strongly shaped by the cultural and socio-economic...
research
∙
03/30/2020
Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering
In this work, we study the utility of graph embeddings to generate laten...
research
∙
03/24/2020
Utilizing Human Memory Processes to Model Genre Preferences for Personalized Music Recommendations
In this paper, we introduce a psychology-inspired approach to model and ...
research
∙
08/12/2019
Evaluating Tag Recommendations for E-Book Annotation Using a Semantic Similarity Metric
In this paper, we present our work to support publishers and editors in ...
research
∙
08/12/2019
Using the Open Meta Kaggle Dataset to Evaluate Tripartite Recommendations in Data Markets
This work addresses the problem of providing and evaluating recommendati...
research
∙
08/02/2019
The Impact of Time on Hashtag Reuse in Twitter: A Cognitive-Inspired Hashtag Recommendation Approach
In our work [KPL17], we study temporal usage patterns of Twitter hashtag...
research
∙
07/23/2019
Modeling Artist Preferences of Users with Different Music Consumption Patterns for Fair Music Recommendations
Music recommender systems have become central parts of popular streaming...
research
∙
06/12/2019
Exploiting weak ties in trust-based recommender systems using regular equivalence
User-based Collaborative Filtering (CF) is one of the most popular appro...
research
∙
01/02/2019
The TagRec Framework as a Toolkit for the Development of Tag-Based Recommender Systems
Recommender systems have become important tools to support users in iden...
research
∙
09/11/2018
Mitigating Confirmation Bias on Twitter by Recommending Opposing Views
In this work, we propose a content-based recommendation approach to incr...
research
∙
09/10/2018
Studying Confirmation Bias in Hashtag Usage on Twitter
The micro-blogging platform Twitter allows its nearly 320 million monthl...
research
∙
08/20/2018
Neighborhood Troubles: On the Value of User Pre-Filtering To Speed Up and Enhance Recommendations
In this paper, we present work-in-progress on applying user pre-filterin...
research
∙
08/14/2018
AFEL-REC: A Recommender System for Providing Learning Resource Recommendations in Social Learning Environments
In this paper, we present preliminary results of AFEL-REC, a recommender...
research
∙
07/18/2018
Trust-Based Collaborative Filtering: Tackling the Cold Start Problem Using Regular Equivalence
User-based Collaborative Filtering (CF) is one of the most popular appro...
research
∙
05/30/2018
Modeling Cognitive Processes in Social Tagging to Improve Tag Recommendations
With the emergence of Web 2.0, tag recommenders have become important to...
research
∙
05/08/2018
Overcoming the Imbalance Between Tag Recommendation Approaches and Real-World Folksonomy Structures with Cognitive-Inspired Algorithms
In this paper, we study the imbalance between current state-of-the-art t...
research
∙
03/08/2018
Modeling Activation Processes in Human Memory to Improve Tag Recommendations
This thesis was submitted by Dr. Dominik Kowald to the Institute of Inte...
research
∙
03/06/2018
The Impact of Semantic Context Cues on the User Acceptance of Tag Recommendations: An Online Study
In this paper, we present the results of an online study with the aim to...
research
∙
11/21/2017
