Generic sentence embeddings provide a coarse-grained approximation of
se...
Most Transformer language models are primarily pretrained on English tex...
Document embeddings and similarity measures underpin content-based
recom...
Transformer-based language models usually treat texts as linear sequence...
Learning scientific document representations can be substantially improv...
Literature recommendation systems (LRS) assist readers in the discovery ...
Recommender systems assist legal professionals in finding relevant liter...
The zbMATH database contains more than 4 million bibliographic entries. ...
Traditional document similarity measures provide a coarse-grained distin...
To cope with the ever-growing information overload, an increasing number...
Recent advances in the area of legal information systems have led to a
v...
In all domains and sectors, the demand for intelligent systems to suppor...
Previous work of ours on Semantic Storytelling uses text analytics proce...
We present a new corpus comprising annotations of medical entities in ca...
Many digital libraries recommend literature to their users considering t...
In this paper, we focus on the classification of books using short
descr...