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Proceedings of the 9th International Workshop on Information Retrieval on Current Research Information Systems

dc.contributor.authorTenreiro De Magalhaes, Sérgio
dc.contributor.authorSantos, Leonel
dc.contributor.authorStempfhuber, Maximilian
dc.contributor.authorFugl, Liv
dc.contributor.authorAlroe, Bo
dc.date.accessioned2015-02-10T12:43:40Z
dc.date.available2015-02-10T12:43:40Z
dc.date.issued2006
dc.description.abstractThe recognition of entities and their relationships in document collections is an important step towards the discovery of latent knowledge as well as to support knowledge management applications. The challenge lies on how to extract and correlate entities, aiming to answer key knowledge management questions, such as; who works with whom, on which projects, with which customers and on what research areas. The present work proposes a knowledge mining approach supported by information retrieval and text mining tasks in which its core is based on the correlation of textual elements through the LRD (Latent Relation Discovery) method. Our experiments show that LRD outperform better than other correlation methods. Also, we present an application in order to demonstrate the approach over knowledge management scenarios.por
dc.identifier.isbn9789729892165
dc.identifier.urihttp://hdl.handle.net/10400.14/16589
dc.language.isoporpor
dc.peerreviewedyespor
dc.publisherUniversidade do Minho, Gáveapt_PT
dc.subjectInformation Retrievalpor
dc.titleProceedings of the 9th International Workshop on Information Retrieval on Current Research Information Systemspor
dc.typebook
dspace.entity.typePublication
oaire.citation.conferencePlaceCopenhagen, Denmarkpor
person.familyNameTenreiro de Magalhaes
person.givenNameSérgio
person.identifier.orcid0000-0002-3338-0236
person.identifier.ridK-6101-2015
person.identifier.scopus-author-id55666780900
rcaap.rightsrestrictedAccesspor
rcaap.typebookpor
relation.isAuthorOfPublicationab41d907-88e5-4279-8dc5-c08a4d5ab296
relation.isAuthorOfPublication.latestForDiscoveryab41d907-88e5-4279-8dc5-c08a4d5ab296

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