24 citations · 47 across the 5 of their papers we have counts for
6 papers
Small data problems in political research: a critical replication study
Hugo de Vos, Suzan Verberne
In an often-cited 2019 paper on the use of machine learning in political research, Anastasopoulos & Whitford (A&W) propose a text classification method for tweets related to organi…
Helping results assessment by adding explainable elements to the deep relevance matching model
Ioannis Chios, Suzan Verberne
In this paper we address the explainability of web search engines. We propose two explainable elements on the search engine result page: a visualization of query term weights and a…
Two tales of science technology linkage: Patent in-text versus front-page references
Jian Wang, Suzan Verberne
There is recurrent debate about how useful science is for technological development, but we know little about what kinds of science are more useful for technology. This paper fills…
Improving reference mining in patents with BERT
Ken Voskuil, Suzan Verberne
In this paper we address the challenge of extracting scientific references from patents. We approach the problem as a sequence labelling task and investigate the merits of BERT mod…
Better Distractions: Transformer-based Distractor Generation and Multiple Choice Question Filtering
Jeroen Offerijns, Suzan Verberne, Tessa Verhoef
For the field of education, being able to generate semantically correct and educationally relevant multiple choice questions (MCQs) could have a large impact. While question genera…
The merits of Universal Language Model Fine-tuning for Small Datasets -- a case with Dutch book reviews
Benjamin van der Burgh, Suzan Verberne
We evaluated the effectiveness of using language models, that were pre-trained in one domain, as the basis for a classification model in another domain: Dutch book reviews. Pre-tra…