---
res:
  bibo_abstract:
  - With the growth in number and variety of RDF datasets comes an in- creasing need
    for both scalable and accurate solutions to support link discovery at instance
    level within and across these datasets. In contrast to ontology matching, most
    linking frameworks rely solely on string similarities to this end. The limited
    use of semantic similarities when linking instances is partly due to the current
    literature stating that they (1) do not improve the F-measure of instance linking
    approaches and (2) are impractical to use because they lack time efficiency. We
    revisit the combination of string and semantic similarities for linking instances.
    Contrary to the literature, our results suggest that this combination can improve
    the F-measure achieved by instance linking systems when the combination of the
    measures is performed by a machine learning approach. To achieve this in- sight,
    we had to address the scalability of semantic similarities. We hence present a
    framework for the rapid computation of semantic similarities based on edge counting.
    This runtime improvement allowed us to run an evaluation of 5 bench- mark datasets.
    Our results suggest that combining string and semantic similarities can improve
    the F-measure by up to 6% absolute.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Kleanthi
      foaf_name: Georgala, Kleanthi
      foaf_surname: Georgala
  - foaf_Person:
      foaf_givenName: Michael
      foaf_name: Röder, Michael
      foaf_surname: Röder
  - foaf_Person:
      foaf_givenName: Mohamed
      foaf_name: Sherif, Mohamed
      foaf_surname: Sherif
      foaf_workInfoHomepage: http://www.librecat.org/personId=67234
    orcid: https://orcid.org/0000-0002-9927-2203
  - foaf_Person:
      foaf_givenName: Axel-Cyrille
      foaf_name: Ngonga Ngomo, Axel-Cyrille
      foaf_surname: Ngonga Ngomo
      foaf_workInfoHomepage: http://www.librecat.org/personId=65716
  dct_date: 2020^xs_gYear
  dct_language: eng
  dct_subject:
  - 2020 dice simba sherif hecate ngonga knowgraphs sys:relevantFor:limboproject limboproject
    sys:relevantFor:infai sys:relevantFor:bis limes limbo opal roeder georgala
  dct_title: 'Applying edge-counting semantic similarities to Link Discovery: Scalability
    and Accuracy@'
...