Open AccessProceedings Article
An Approach to Text Corpus Construction which Cuts Annotation Costs and Maintains Reusability of Annotated Data
Katrin Tomanek,Joachim Wermter,Udo Hahn +2 more
- pp 486-495
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TLDR
The issue whether a corpus annotated by means of AL can be re-used to train classifiers different from the ones employed by AL, supplying alternative feature sets as well is addressed.Abstract:
We consider the impact Active Learning (AL) has on effective and efficient text corpus annotation, and report on reduction rates for annotation efforts ranging up until 72%. We also address the issue whether a corpus annotated by means of AL ‐ using a particular classifier and a particular feature set ‐ can be re-used to train classifiers different from the ones employed by AL, supplying alternative feature sets as well. We, finally, report on our experience with the AL paradigm under real-world conditions, i.e., the annotation of large-scale document corpora for the life sciences.read more
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References
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