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Issue No.04 - July-Aug. (2013 vol.15)
pp: 66-74
Steffen Koch , University of Stuttgart
Florian Heimerl , University of Stuttgart
Thomas Ertl , University of Stuttgart
ABSTRACT
An interactive method combines visualization and machine learning to improve complex document retrieval tasks.
INDEX TERMS
Document handling, Information retrieval, Search methods, Data visualization,scientific computing, interactive visualization, visual analytics, document search, information retrieval, machine learning, binary classifier
CITATION
Steffen Koch, Florian Heimerl, Thomas Ertl, "Visual Document Retrieval: Supporting Text Search and Analysis with Visual Analytics", Computing in Science & Engineering, vol.15, no. 4, pp. 66-74, July-Aug. 2013, doi:10.1109/MCSE.2013.93
REFERENCES
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2. D. Keim et al., Mastering the Information Age: Solving Problems with Visual Analytics, Eurographics Assoc., 2010.
3. C.D. Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval, Cambridge Univ. Press, 2008.
4. F. Heimerl et al., “Visual Classifier Training for Text Document Retrieval,” IEEE Trans. Visualization and Computer Graphics, vol. 18, no. 12, 2012, pp. 2839-2848.
5. S. Koch et al., “Iterative Integration of Visual Insights during Scalable Patent Search and Analysis,” IEEE Trans. Visualization and Computer Graphics, vol. 17, no. 5, 2011, pp. 557-569.
6. B. Settles, Active Learning, Morgan & Claypool, 2012.
7. F.V. Paulovich, C.T. Silva, and L.G. Nonato, “User-Centered Multidimensional Projection Techniques,” Computing in Science & Eng., vol. 14, no. 4, 2012, pp. 74-81.
8. G. Andrienko et al., “Discovering Thematic Patterns in Geo-Referenced Tweets through Space-Time Visual Analytics,” Computing in Science & Eng., vol. 15, no. 3, 2013, pp. 72-82.
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