Active feature acquisition for opinion stream classification under drift

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dc.identifier.uri Shivakumaraswamy, Ranjith Beyer, Christian Unnikrishnan, Vishnu Ntoutsi, Eirini Spiliopoulou, Myra 2020-05-18T09:16:27Z 2020-05-18T09:16:27Z 2019
dc.identifier.citation Shivakumaraswamy, R.; Beyer, C.; Unnikrishnan, V.; Ntoutsi, Eirini; Spiliopoulou, M.: Active feature acquisition for opinion stream classification under drift. In: CEUR Workshop Proceedings 2444 (2019), S. 108-111.
dc.description.abstract Active stream learning is frequently used to acquire labels for instances and less frequently to determine which features should be considered as the stream evolves. We introduce a framework for active feature selection, intended to adapt the feature space of a polarity learner over a stream of opinionated documents. We report on the first results of our framework on substreams of reviews on different product categories. eng
dc.language.iso eng
dc.publisher Aachen : RWTH
dc.relation.ispartofseries CEUR Workshop Proceedings 2444 (2019)
dc.rights CC BY 4.0 Unported
dc.subject Active Feature Acquisition eng
dc.subject Opinion Stream Classification eng
dc.subject Feature acquisition eng
dc.subject Feature space eng
dc.subject Product categories eng
dc.subject Stream classification eng
dc.subject Sub-streams eng
dc.subject Classification (of information) eng
dc.subject.ddc 004 | Informatik ger
dc.title Active feature acquisition for opinion stream classification under drift eng
dc.type article
dc.type Text
dc.relation.issn 1613-0073
dc.bibliographicCitation.volume 2444
dc.bibliographicCitation.firstPage 108
dc.bibliographicCitation.lastPage 111
dc.description.version publishedVersion
tib.accessRights frei zug�nglich

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