This data relates to our paper "Stereotype and Most-Popular Recommendations in the Digital Library Sowiport". The data includes a list of the 28 million delivered and clicked recommendations as CSV file, the R script to analyze the data, and the figures and tables presented in this paper as PNG and CSV files. This open access to the data allows replicating our analyses, checking the results for correctness, and conducting additional analyses
Typically, recommendation algorithms are unable to make recommendations for new users due to the inh...
Within this paper we present our contribution to Task 2 of the ESWC’14 Recommender Systems Challenge...
This repository contains the full set of data (14 CSVs) used in the study "Investigating automated p...
Stereotype and most-popular recommendations are widely neglected in the research-paper recommender ...
This data relates to the paper "Position Bias in Recommender Systems for Digital Libraries". During ...
This data relates to our paper "Extending a Research-Paper Recommendation System with Scientometric ...
We introduce RARD, the Related-Article Recommendation Dataset, from the digital library Sowiport and...
A Recommendation engine recommends the most relevant items to the user by using different algorithms...
Recommender Systems in Light of Big Data is a research paper extracted from my master thesis.</p
This repository contains three datasets for evaluating accuracy, miscalibration and popularity lift ...
With the growing amount of information online, recommender systems are used widely as a strategic ap...
Four multimedia recommender systems datasets to study popularity bias and fairness: Last.fm (lfm....
This file contains the experimental scripts from the paper \u27Recommender Response to Diversity and...
This paper presents a novel approach to automated product recommendation based on the popularity cha...
Typically, recommendation algorithms are unable to make recommendations for new users due to the inh...
Typically, recommendation algorithms are unable to make recommendations for new users due to the inh...
Within this paper we present our contribution to Task 2 of the ESWC’14 Recommender Systems Challenge...
This repository contains the full set of data (14 CSVs) used in the study "Investigating automated p...
Stereotype and most-popular recommendations are widely neglected in the research-paper recommender ...
This data relates to the paper "Position Bias in Recommender Systems for Digital Libraries". During ...
This data relates to our paper "Extending a Research-Paper Recommendation System with Scientometric ...
We introduce RARD, the Related-Article Recommendation Dataset, from the digital library Sowiport and...
A Recommendation engine recommends the most relevant items to the user by using different algorithms...
Recommender Systems in Light of Big Data is a research paper extracted from my master thesis.</p
This repository contains three datasets for evaluating accuracy, miscalibration and popularity lift ...
With the growing amount of information online, recommender systems are used widely as a strategic ap...
Four multimedia recommender systems datasets to study popularity bias and fairness: Last.fm (lfm....
This file contains the experimental scripts from the paper \u27Recommender Response to Diversity and...
This paper presents a novel approach to automated product recommendation based on the popularity cha...
Typically, recommendation algorithms are unable to make recommendations for new users due to the inh...
Typically, recommendation algorithms are unable to make recommendations for new users due to the inh...
Within this paper we present our contribution to Task 2 of the ESWC’14 Recommender Systems Challenge...
This repository contains the full set of data (14 CSVs) used in the study "Investigating automated p...