Feature-Based Visual Exploration of Text Classification

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Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015. 2015
Zusammenfassung

There are many applications of text classification such as gender attribution in market research or the identification of forged product reviews on e-commerce sites. Although several automatic methods provide satisfying performance in most application cases, we see a gap in supporting the analyst to understand the results and derive knowledge for future application scenarios. In this paper, we present a visualization driven application that allows analysts to gain insight in text classification tasks such as sentiment detection or authorship attribution on feature level, built with a practitioner’s way of reasoning in mind, the Text Classification Analysis Process.

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Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015, 26. Okt. 2015, Chicago, Illinois
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ISO 690STOFFEL, Florian, Lucie FLEKOVA, Daniela OELKE, Iryna GUREVYCH, Daniel A. KEIM, 2015. Feature-Based Visual Exploration of Text Classification. Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015. Chicago, Illinois, 26. Okt. 2015. In: Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015. 2015
BibTex
@inproceedings{Stoffel2015Featu-45096,
  year={2015},
  title={Feature-Based Visual Exploration of Text Classification},
  url={https://scibib.dbvis.de/publications/view/634},
  booktitle={Symposium on Visualization in Data Science (VDS) at IEEE VIS 2015},
  author={Stoffel, Florian and Flekova, Lucie and Oelke, Daniela and Gurevych, Iryna and Keim, Daniel A.}
}
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