Paper recommender systems: a literature survey
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 …
recommender systems. We reviewed these articles and present some descriptive statistics in …
An anatomization of research paper recommender system: Overview, approaches and challenges
The purpose of this study is to present an exhaustive analysis on research paper
recommender systems which have become very popular and gained a lot of research …
recommender systems which have become very popular and gained a lot of research …
Psychology-informed recommender systems
Personalized recommender systems have become indispensable in today's online world.
Most of today's recommendation algorithms are data-driven and based on behavioral data …
Most of today's recommendation algorithms are data-driven and based on behavioral data …
A comparison of offline evaluations, online evaluations, and user studies in the context of research-paper recommender systems
J Beel, S Langer - Research and Advanced Technology for Digital …, 2015 - Springer
The evaluation of recommender systems is key to the successful application of
recommender systems in practice. However, recommender-systems evaluation has received …
recommender systems in practice. However, recommender-systems evaluation has received …
Towards reproducibility in recommender-systems research
J Beel, C Breitinger, S Langer, A Lommatzsch… - User modeling and user …, 2016 - Springer
Numerous recommendation approaches are in use today. However, comparing their
effectiveness is a challenging task because evaluation results are rarely reproducible. In this …
effectiveness is a challenging task because evaluation results are rarely reproducible. In this …
[PDF][PDF] TF-IDuF: a novel term-weighting scheme for user modeling based on users' personal document collections
TF-IDF is one of the most popular term-weighting schemes, and is applied by search
engines, recommender systems, and user modeling engines. With regard to user modeling …
engines, recommender systems, and user modeling engines. With regard to user modeling …
Towards effective research-paper recommender systems and user modeling based on mind maps
J Beel - arXiv preprint arXiv:1703.09109, 2017 - arxiv.org
While user-modeling and recommender systems successfully utilize items like emails, news,
and movies, they widely neglect mind-maps as a source for user modeling. We consider this …
and movies, they widely neglect mind-maps as a source for user modeling. We consider this …
[图书][B] Stereotype and most-popular recommendations in the digital library sowiport
Stereotype and most-popular recommendations are widely neglected in the research-paper
recommender system and digital-library community. In other domains such as movie …
recommender system and digital-library community. In other domains such as movie …
RARD: the related-article recommendation dataset
Recommender-system datasets are used for recommender-system evaluations, training
machine-learning algorithms, and exploring user behavior. While there are many datasets …
machine-learning algorithms, and exploring user behavior. While there are many datasets …
[PDF][PDF] Evaluating the CC-IDF citation-weighting scheme: how effectively can 'Inverse Document Frequency'(IDF) be applied to references
J Beel, C Breitinger, S Langer - Proceedings of the 12th …, 2017 - researchgate.net
In the domain of academic search engines and research-paper recommender systems, CC-
IDF is a common citation-weighting scheme that is used to calculate semantic relatedness …
IDF is a common citation-weighting scheme that is used to calculate semantic relatedness …