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Erschienen in:
2012 | OriginalPaper | Buchkapitel
ASV Monitor: Creating Comparability of Machine Learning Methods for Content Analysis
verfasst von : Andreas Niekler, Patrick Jähnichen, Gerhard Heyer
Erschienen in: Machine Learning and Knowledge Discovery in Databases
Verlag: Springer Berlin Heidelberg
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In this demonstration paper we present an application to compare and evaluate machine learning methods used for natural language processing within a content analysis framework. Our aim is to provide an example set of possible machine learning results for different inputs to increase the acceptance of using machine learning in settings that originally rely on manual treatment. We will demonstrate the possibility to compare machine learning algorithms regarding the outcome of the implemented approaches. The application allows the user to evaluate the benefit of using machine learning algorithms for content analysis by a visual comparison of their results.