A preliminary assessment of the article deduplication algorithm used for the OpenAIRE Research Graph
IRCDL 2022
2022
Conference/Workshop
- Contact persons: Ilias Kanellos , Serafeim Chatzopoulos , Thanasis Vergoulis
Abstract.
n recent years, a large number of Scholarly Knowledge Graphs (SKGs) have been introduced in the
literature. The communities behind these graphs strive to gather, clean, and integrate scholarly metadata
from various sources to produce clean and easy-to-process knowledge graphs. In this context, a very
important task of the respective cleaning and integration workflows is deduplication. In this paper,
we briefly describe and evaluate the accuracy of the deduplication algorithm used for the OpenAIRE
Research Graph. Our experiments show that the algorithm has an adequate performance producing a
small number of false positives and an even smaller number of false negatives.