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dc.contributor.authorHerzig, Daniel Markus*
dc.date.accessioned2021-02-12T00:48:41Z
dc.date.available2021-02-12T00:48:41Z
dc.date.issued2014*
dc.date.submitted2019-07-30 20:01:58*
dc.identifier34452*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/57610
dc.description.abstractRanking - the algorithmic decision on how relevant an information artifact is for a given information need and the sorting of artifacts by their concluded relevancy - is an integral part of every search engine. In this book we investigate how structured Web data can be leveraged for ranking with the goal to improve the effectiveness of search. We propose new solutions for ranking using on-the-fly data integration and experimentally analyze and evaluate them against the latest baselines.*
dc.languageEnglish*
dc.subjectQA75.5-76.95*
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer scienceen_US
dc.subject.othersearch*
dc.subject.otherinformation retrieval*
dc.subject.otherweb data*
dc.subject.othersemantic search*
dc.titleRanking for Web Data Search Using On-The-Fly Data Integration*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000037230*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
oapen.relation.isbn9783731501367*
oapen.pagesVII, 202 p.*
peerreview.review.typeFull text
peerreview.anonymityAll identities known
peerreview.reviewer.typeInternal editor
peerreview.reviewer.typeExternal peer reviewer
peerreview.review.stagePre-publication
peerreview.open.reviewNo
peerreview.publish.responsibilityScientific or Editorial Board
peerreview.id8ad5c235-9810-49eb-b358-27c8675324d9
peerreview.titleDissertations (Dissertationen)


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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-sa/4.0/