8 citations · 12 across the 3 of their papers we have counts for
10 papers
NaïveRole: Author-Contribution Extraction and Parsing from Biomedical Manuscripts
Dominika Tkaczyk, Andrew Collins, Joeran Beel
Information about the contributions of individual authors to scientific publications is important for assessing authors' achievements. Some biomedical publications have a short sec…
ParsRec: A Novel Meta-Learning Approach to Recommending Bibliographic Reference Parsers
Dominika Tkaczyk, Rohit Gupta, Riccardo Cinti +1
Bibliographic reference parsers extract machine-readable metadata such as author names, title, journal, and year from bibliographic reference strings. To extract the metadata, the…
Hybrid Approach to Automation, RPA and Machine Learning: a Method for the Human-centered Design of Software Robots
Wiesław Kopeć, Marcin Skibiński, Cezary Biele +6
One of the more prominent trends within Industry 4.0 is the drive to employ Robotic Process Automation (RPA), especially as one of the elements of the Lean approach. The full imple…
ParsRec: Meta-Learning Recommendations for Bibliographic Reference Parsing
Dominika Tkaczyk, Paraic Sheridan, Joeran Beel
Bibliographic reference parsers extract metadata (e.g. author names, title, year) from bibliographic reference strings. No reference parser consistently gives the best results in e…
One-at-a-time: A Meta-Learning Recommender-System for Recommendation-Algorithm Selection on Micro Level
Andrew Collins, Dominika Tkaczyk, Joeran Beel
The effectiveness of recommendation algorithms is typically assessed with evaluation metrics such as root mean square error, F1, or click through rates, calculated over entire data…
A Study of Position Bias in Digital Library Recommender Systems
Andrew Collins, Dominika Tkaczyk, Akiko Aizawa +1
"Position bias" describes the tendency of users to interact with items on top of a list with higher probability than with items at a lower position in the list, regardless of the i…