ACM/IEEE Joint Conference on Digital Libraries 2018

ACM/IEEE Joint Conference on Digital Libraries 2018 is mostly related to scientific communities from diverse domains such as data science/analytics, data curation/stewardship, information retrieval, human-computer interaction, hypertext (and Web/network science), multimedia, publishing, preservation, digital humanities, machine learning/AI, heritage/culture, health/medicine, policy, law, and privacy/intellectual property.

MOVING successfully participated with two full research papers in the conference. More specifically,  Florian Mai from ZBW presented the full paper “Using Deep Learning for Title-Based Semantic Subject Indexing to Reach Competitive Performance to Full-Text” on Tuesday, June 5, in the session on text collections.Florian’s talk showed that for scientific digital libraries automatic subject indexing methods based on the title of a publication can be as good as or even better than the full-text-based methods by leveraging the surplus of data available to train powerful neural network models. Using titles only is important as this information is usually freely available while full-text may be subject to license.Tobias Backes from GESIS presented the full paper “Effective Unsupervised Author Disambiguation with Relative Frequencies” on Tuesday, June 5, in the session on exploring and analyzing collections. Tobias’s talk presented the problem of author name homonymy in the Web of Science and introduced a novel probabilistic similarity measure for author name disambiguation based on feature overlap.