Authormagic: an approach to author disambiguation in large-scale digital libraries

Authors:
Henning Weiler;Klaus Meyer-Wegener;Salvatore Mele
Affiliations:
University Erlangen-Nuremberg and CERN, Erlangen, Germany;University Erlangen-Nuremberg, Erlangen, Germany;CERN, Geneva, Switzerland
Venue:
Proceedings of the 20th ACM international conference on Information and knowledge management
Year:
2011

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Abstract

A collaboration of leading research centers in the field of High Energy Physics (HEP) has built INSPIRE, a novel information infrastructure, which comprises the entire corpus of about one million documents produced within the discipline, including a rich set of metadata, citation information and half a million full-text documents, and offers a unique opportunity for author disambiguation strategies. The presented approach features extended metadata comparison metrics and a three-step unsupervised graph clustering technique. The algorithm aided in identifying 200'000 individuals from 6'500'000 author signatures. Preliminary tests based on knowledge of external experts and a pilot of a crowd-sourcing system show a success rate of more than 96% within the selected test cases. The obtained author clusters serve as a recommendation for INSPIRE users to further clean the publication list in a crowd-sourced approach.