Mining postal addresses

dc.contributor.authorCortizo Pérez, José Carlos
dc.contributor.authorGómez Hidalgo, José María
dc.contributor.authorTemprado Rodríguez, Yaiza
dc.contributor.authorMartín, Diego
dc.contributor.authorRodríguez, Federico
dc.contributor.otherWeghorn, Hans
dc.contributor.otherAbraham, Ajith
dc.date.accessioned2016-07-15T16:20:33Z
dc.date.available2016-07-15T16:20:33Z
dc.date.issued2008
dc.description.abstractThis paper presents FuMaS (Fuzzy Matching System), a system capable of an efficient retrieval of postal addresses from noisy queries. The fuzzy postal addresses retrieval has many possible applications, ranging from datawarehouse dedumping, to the correction of input forms, or the integration within online street directories, etc. This paper presents the system architecture along with a series of experiments performed using FuMaS. The experimental results show that FuMaS is a very useful system when retrieving noisy postal addresses, being able to retrieve almost 85% of the total ones. This represents an improvement of the 15% when comparing with other systems tested in this set of experiments.spa
dc.description.filiationUEMspa
dc.description.impactNo data (2008)spa
dc.description.sponsorshipSin financiaciónspa
dc.identifier.citationCortizo, J. C., Gómez, J. M., Temprado, Y., Martín, D., & Rodríguez, F. (2008). Mining postal addresses. In H. Weghorn & A.P. Abraham (Eds.), IADIS European Conference Data Mining (pp. 67-72). Amsterdam, Netherlands: IADIS.spa
dc.identifier.isbn9789728924638
dc.identifier.urihttp://hdl.handle.net/11268/5414
dc.language.isoengspa
dc.peerreviewedSispa
dc.publisherIADISspa
dc.rights.accessRightsrestricted accessen
dc.subject.otherIADIS European Conference Data Miningspa
dc.subject.uemRecuperación de la informaciónspa
dc.subject.unescoAplicación informáticaspa
dc.titleMining postal addressesspa
dc.typeconference outputspa
dspace.entity.typePublication
relation.isAuthorOfPublicatione1ae5b27-3248-41df-ac24-a38ed621e0f9
relation.isAuthorOfPublication76a395e8-090d-4187-9a3c-420063e1f44f
relation.isAuthorOfPublication.latestForDiscoverye1ae5b27-3248-41df-ac24-a38ed621e0f9

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