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Discovering related scientific literature beyond semantic similarity: a new co-citation approach

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dc.contributor.authorRodríguez Prieto, Oscar
dc.contributor.authorAraujo Serna, M. Lourdes
dc.contributor.authorMartínez Romo, Juan
dc.date.accessioned2024-06-11T15:15:28Z
dc.date.available2024-06-11T15:15:28Z
dc.date.issued2019-05-17
dc.description.abstractWe propose a new approach to recommend scientific literature, a domain in which the efficient organization and search of information is crucial. The proposed system relies on the hypothesis that two scientific articles are semantically related if they are co-cited more frequently than they would be by pure chance. This relationship can be quantified by the probability of co-citation, obtained from a null model that statistically defines what we consider pure chance. Looking for article pairs that minimize this probability, the system is able to recommend a ranking of articles in response to a given article. This system is included in the co-occurrence paradigm of the field. More specifically, it is based on co-cites so it can produce recommendations more focused on relatedness than on similarity. Evaluation has been performed on the ACL Anthology collection and on the DBLP dataset, and a new corpus has been compiled to evaluate the capacity of the proposal to find relationships beyond similarity. Results show that the system is able to provide, not only articles similar to the submitted one, but also articles presenting other kind of relations, thus providing diversity, i.e. connections to new topics.en
dc.description.versionversión publicada
dc.identifier.doihttps://doi.org/10.1007/s11192-019-03125-9
dc.identifier.issn0138-9130; eISSN: 1588-2861
dc.identifier.urihttps://hdl.handle.net/20.500.14468/22413
dc.journal.titleScientometrics
dc.journal.volume120
dc.language.isoen
dc.publisherSpringer
dc.relation.centerE.T.S. de Ingeniería Informática
dc.relation.departmentLenguajes y Sistemas Informáticos
dc.rightsAtribución 4.0 Internacional
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subject.keywordsScientific related literature
dc.subject.keywordsrecommendations
dc.subject.keywordsco-citation
dc.subject.keywordsstatistical model
dc.subject.keywordssemantic similarity
dc.titleDiscovering related scientific literature beyond semantic similarity: a new co-citation approaches
dc.typeartículoes
dc.typejournal articleen
dspace.entity.typePublication
relation.isAuthorOfPublication77c4023e-4374-442a-9dfb-b9d4b609c31e
relation.isAuthorOfPublication91b7e317-2a30-494f-98e9-3a0e026747b1
relation.isAuthorOfPublication.latestForDiscovery77c4023e-4374-442a-9dfb-b9d4b609c31e
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