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dc.contributor.authorHulpus, Ioana
dc.contributor.authorPrangnawarat, Narumol
dc.contributor.authorHayes, Conor
dc.identifier.citationHulpus, Ioana, Prangnawarat, Narumol, & Hayes, Conor. (2015). Path-based semantic relatedness on linked data and its use to word and entity disambiguation. Paper presented at the International Semantic Web Conference, United States.
dc.description.abstractSemantic relatedness and disambiguation are fundamental problems for linking text documents to the Web of Data. There are many approaches dealing with both problems but most of them rely on word or concept distribution over Wikipedia. They are therefore not applicable to concepts that do not have a rich textual description. In this paper, we show that semantic relatedness can also be accurately computed by analysing only the graph structure of the knowledge base. In addition, we propose a joint approach to entity and word-sense disambiguation that makes use of graph-based relatedness. As opposed to the majority of state-of-the-art systems that target mainly named entities, we use our approach to disambiguate both entities and common nouns. In our experiments, we first validate our relatedness measure on multiple knowledge bases and ground truth datasets and show that it performs better than related state-of-the-art graph based measures. Afterwards, we evaluate the disambiguation algorithm and show that it also achieves superior disambiguation accuracy with respect to alternative state-of-the- art graph-based algorithms.en_US
dc.relation.ispartofInternational Semantic Web Conferenceen
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Ireland
dc.subjectLinked dataen_US
dc.subjectEntity disambiguationen_US
dc.subjectPath-based semantic relatednessen_US
dc.titlePath-based semantic relatedness on linked data and its use to word and entity disambiguationen_US
dc.typeConference Paperen_US
dc.contributor.funder|~|Science Foundation Ireland (SFI)|~|
dc.local.contactIoana Rodica Hulpus, Insight, Nui Galway. Email:

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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Ireland