Resource – Paper 308
| José Eduardo Talavera Herrera, Marco Antonio Casanova, Bernardo Pereira Nunes, Luiz André P. Paes Leme and Giseli Rabello LopesResource
October 23, 2017, 15:00. Lehár 4 Download paper (preprint) |
Abstract
A knowledge base stores descriptions of entities and their relationships, often in the form of a very large RDF graph, such as DBpedia or Wikidata. The entity relatedness problem refers to the question of computing the relationship paths that better capture the connectivity between a given entity pair. This paper describes a dataset created to support the evaluation of approaches that address the entity relatedness problem. The dataset covers two familiar domains, music and movies, and uses data available in IMDb and last.fm, which are popular reference datasets in these domains. The paper describes in
detail how sets of entity pairs from each of these domains were selected and, for each entity pair, how a ranked list of relationship paths was obtained.
won’t defining entity relatedness by means of graphs (with restrictions) introduce biases?
How likely is it that the presented approach generalizes to other domains, given that it’s only focusing on the (very similar) movie and music domain?
related work could be improved, how does this work compare to:
– https://dl.acm.org/citation.cfm?id=2874488
– https://hpi.de/fileadmin/user_upload/fachgebiete/meinel/papers/Web_3.0/2015_BobicWaitelonisSack.pdf
– https://link.springer.com/chapter/10.1007%2F978-3-540-88564-1_39?LI=true
– http://www.aaai.org/Papers/IJCAI/2007/IJCAI07-259.pdf
– https://dl.acm.org/citation.cfm?id=1708133
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