Petr Knoth

Online Evaluations for Everyone: Mr. DLib's Living Lab for Scholarly Recommendations

2018 · arXiv

We introduce the first 'living lab' for scholarly recommender systems. This lab allows recommender-system researchers to conduct online evaluations of their novel algorithms for scholarly recommendations, i.e., recommendations for research papers, citations, conferences, research grants, …

Building recommender systems for scholarly information

2017

The depth and breadth of research now being published is overwhelming for an individual researcher to keep track of let alone consume. Recommender systems have been developed to make it easier for researchers to discover …

Confidence estimation of classification based on the distribution of the neural network output layer

2022 · arXiv (Cornell University)

One of the most common problems preventing the application of prediction models in the real world is lack of generalization: The accuracy of models, measured in the benchmark does repeat itself on future data, e.g. …