Digital libraries maintain extensive collections of knowledge and need to provide effective access paths for their users. For instance, PubPharm, the specialized information service for Pharmacy in Germany, provides and develops access paths to their underlying biomedical document collection. In brief, PubPharm supports traditional keyword-based search, search for chemical structures, as well as novel graph-based discovery workflows, e.g., listing or searching for interactions between different pharmaceutical entities. This paper introduces a new search functionality, called narrative pattern mining, allowing users to explore context-relevant entities and entity interactions. We performed interviews with five domain experts to verify the usefulness of our prototype.
@article{arxiv.2509.09687,
title = {Demonstrating Narrative Pattern Discovery from Biomedical Literature},
author = {Hermann Kroll and Pascal Sackhoff and Bill Matthias Thang and Christin Katharina Kreutz and Wolf-Tilo Balke},
journal= {arXiv preprint arXiv:2509.09687},
year = {2025}
}