Active feature acquisition for opinion stream classification under drift

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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.

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/9818

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Sum total of downloads: 84




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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.
License of this version: CC BY 4.0 Unported
Document Type: article
Publishing status: publishedVersion
Issue Date: 2019
Appears in Collections:Fakultät für Elektrotechnik und Informatik

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 36 42.86%
2 image of flag of United States United States 19 22.62%
3 image of flag of Brazil Brazil 11 13.10%
4 image of flag of India India 3 3.57%
5 image of flag of Iran, Islamic Republic of Iran, Islamic Republic of 2 2.38%
6 image of flag of Hong Kong Hong Kong 2 2.38%
7 image of flag of China China 2 2.38%
8 image of flag of Vietnam Vietnam 1 1.19%
9 image of flag of No geo information available No geo information available 1 1.19%
10 image of flag of Taiwan Taiwan 1 1.19%
    other countries 6 7.14%

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