Reducing Large Semantic Graphs to Improve Semantic Relatedness

dc.contributor.author Teresa Almeida Costa en
dc.contributor.author José Paulo Leal en
dc.date.accessioned 2017-12-19T19:33:52Z
dc.date.available 2017-12-19T19:33:52Z
dc.date.issued 2015 en
dc.description.abstract In the previous research the authors developed a family of semantic measures that are adaptable to any semantic graph, being automatically tuned with a set of parameters. The research presented in this paper extends this approach by also tuning the graph. This graph reduction procedure starts with a disconnected graph and incrementally adds edge types, until the quality of the semantic measure cannot be further improved. The validation performed used the three most recent versions of WordNet and, in most cases, this approach improves the quality of the semantic measure. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/4327
dc.identifier.uri http://dx.doi.org/10.1007/978-3-319-27653-3_23 en
dc.language eng en
dc.relation 5125 en
dc.relation 5935 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Reducing Large Semantic Graphs to Improve Semantic Relatedness en
dc.type conferenceObject en
dc.type Publication en
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