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dc.contributor.authorBlohm, Sebastian*
dc.date.accessioned2021-02-11T17:27:53Z
dc.date.available2021-02-11T17:27:53Z
dc.date.issued2010*
dc.date.submitted2019-07-30 20:01:57*
dc.identifier34410*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/51420
dc.description.abstractExtracting information from text is the task of obtaining structured, machine-processable facts from information that is mentioned in an unstructured manner. It thus allows systems to automatically aggregate information for further analysis, efficient retrieval, automatic validation, or appropriate visualization. This work explores the potential of using textual patterns for Information Extraction from the World Wide Web.*
dc.languageEnglish*
dc.subjectHF5001-6182*
dc.subject.classificationbic Book Industry Communication::K Economics, finance, business & management::KJ Business & management::KJC Business strategyen_US
dc.subject.otherInformation Extraction*
dc.subject.otherData Mining*
dc.subject.otherPattern Induction*
dc.subject.otherWeb Mining*
dc.subject.otherMachine Learning*
dc.titleLarge-Scale Pattern-Based Information Extraction from the World Wide Web*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000015694*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
oapen.relation.isbn9783866444799*
oapen.pagesVII, 236 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-nc-nd/4.0/