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dc.contributor.authorVincent, Dominique*
dc.date.accessioned2021-02-11T13:12:42Z
dc.date.available2021-02-11T13:12:42Z
dc.date.issued2015*
dc.date.submitted2019-07-30 20:02:00*
dc.identifier35210*
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/47143
dc.description.abstractIn this work a model is engineered to depict topic relationships as graphs between detected topics of different time windows. By varying and shifting the time span of consideration the relationships between topics can be mapped with a variable complexity including the topic frequencies. Topic life cycles as well as changes in thematic relationships and their evolution become perceptible. Topics found can be matched in structure as well as their temporal progression to existing events.*
dc.languageGerman*
dc.subjectHF5001-6182*
dc.subject.otherThemen-Frequenz*
dc.subject.otherdocument streams*
dc.subject.otherThemen-Graphen*
dc.subject.otherDokumentenstrom*
dc.subject.othertopic-graph*
dc.subject.othertext mining*
dc.subject.otherText Mining*
dc.subject.othertopic-frequency*
dc.titleEvolution von Relationen in temporalen partiten Themen-Graphen*
dc.typebook
oapen.identifier.doi10.5445/KSP/1000045521*
oapen.relation.isPublishedBy68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2*
virtual.oapen_relation_isPublishedBy.publisher_nameKIT Scientific Publishing
virtual.oapen_relation_isPublishedBy.publisher_websitehttp://www.ksp.kit.edu/
oapen.relation.isbn9783731503408*
oapen.pagesII, 136 p.*


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