Abstract
In big data analytics, visualization and access are central for the creation of knowledge and value from data. Interactive visualizations of analysis of structured data are commonplace. In this paper, information visualization and interaction for text analysis are addressed. The paper motivates this issue from a data usage standpoint, gives a survey of approaches in the area of interactive visualization of text analytics, and presents our proposal of a specific solution design for visual interaction with results from a combination of named entity recognition (NER) and text categorization (TC). This matrix-based model illustrates abstract views on complex relationships between abstract entities and is exemplary for any combination of feature extraction and TC. The aim of our proposal is to support feature extraction and TC researchers in distributed virtual research environments by providing intuitive visual interfaces.
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References
Balog, K., Serdyukov, P., de Vries, A.P.: Overview of the TREC 2010 entity track. In: Proceedings of the Nineteenth Text REtrieval Conference (TREC). NIST (NIST Special Publication, SP 500–294) (2010)
Bertin, J.: Sémiologie Graphique, Editions Gauthier-Villars (1967). Paris, France (German translation Jensch, G., Schade, D., Scharfe, W. Graphische Semiologie. Diagramme Netze Karten Berlin (1974)
Blei, D.M., Ng, A.Y., Jordan, M.I., Lafferty, J.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3(45), 993–1022 (2003). doi:10.1162/jmlr.2003.3.4-5.993
Bornschlegl, M.X., Berwind, K., Kaufmann, M., Engel, F., Walsh, P., Hemmje, M.L., Riestra, R.: IVIS4BigData: a reference model for advanced visual interfaces supporting big data analysis in virtual research environments (2016)
Candela, L., Castelli, D., Pagano, P.: Virtual research environments: an overview and a research agenda. Data Sci. J. 12, grdi75–grdi81 (2013). http://doi.org/10.2481/dsj.GRDI013
Card, S.K., Mackinlay, J.D., Shneiderman, B. (eds.): Readings in Information Visualization: Using Vision to Think. Morgan Kaufmann Publishers Inc., San Francisco (1999)
Chuang, J., Manning, C.D., Heer, J.: Termite: visualization techniques for assessing textual topic models. In: Proceedings of the International Working Conference on Advanced Visual Interfaces, pp. 74–77 (2012)
Demchenko, Y., Grosso, P., de Laat, C., Membrey, P.: Addressing big data issues in scientific data infrastructure. In: International Conference on Collaboration Technologies and Systems (CTS), p. 4855 (2013)
Dou, W., Wang, X., Skau, D., Ribarsky, W., Zhou, M.X.: LeadLine: interactive visual analysis of text data through event identification and exploration. In: IEEE Conference on Visual Analytics Science and Technology (VAST) (2012)
Grinstein, G., Trutschl, M., Cvek, U.: High Dimensional Visualization Institute for Visualization and Perception Research, University of Massachusetts Lowell (2001). http://www.cs.uml.edu/mtrutsch/research/High-Dimensional_Visualizations-KDD2001-color.pdf
Jurafsky, D., Martin, J.H.: Speech and language processing. In: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition. Prentice Hall series in artificial intelligence, 2nd edn. Pearson Prentice Hall, Upper Saddle (2009)
Kaufmann, M.: Towards a reference model for big data management. Research report, Faculty of Mathematics, Computer Science, University of Hagen. https://ub-deposit.fernuni-hagen.de/receive/mir_mods_00000583. Accessed 4 July 2016
Larsen, P.O., Ins, M.: The rate of growth in scientific publication and the decline in coverage by science citation index. Scientometrics 84(3), 575–603 (2010). Springer
MLib documentation. http://spark.apache.org/docs/latest/mllib-guide.html. Accessed 28 Feb
Mohri, M., Rostamizadeh, A., Talwalkar, A.: Foundations of Machine Learning. MIT Press, Cambridge (2012)
Nawroth, C., Schmedding, M., Brocks, H., Kaufmann, M., Fuchs, M., Hemmje, M.L.: Toward cloud-based knowledge capturing based on natural language processing. In: Machine Learning in Automated Text Categorization. HOLACONF - Cloud Forward: From Distributed to Complete Computing (2015)
NIST Special Publication 1500–6, NIST Big Data Interoperability Framework, vol. 6. Reference Architecture. http://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.Spp.1500-6.pdf. Accessed 7 Apr 2016
Sebastiani, F.: Machine learning in automated text categorization. ACM Comput. Surv. 34, 1–47 (2002)
Singh, D., Reddy, C.K.: Survey on platforms for big data analytics. J. Big Data (2012). http://www.journalofbigdata.com/content/1/1/8. Accessed 28 Feb 2016
Stasko, J., Gärg, C., Liu, Z.: Jigsaw: supporting investigative analysis through interactive visualization. Inf. Vis. 7(2), 118–132 (2008)
Swoboda, S., Kaufmann, M., Hemmje, M.L.: Toward cloud-based classification and annotation support. In: Proceedings of the 6th International Conference on Cloud Computing and Services Science (CLOSER 2016), vol. 2, pp. 131–137 (2016)
Wei, F., Liu, S., Song, Y., Pan, S., Zhou, M.X., Qian, W.: TIARA: a visual exploratory text analytic system. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 153–162 (2010)
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Swoboda, T., Nawroth, C., Kaufmann, M., Hemmje, M.L. (2016). Toward Interactive Visualization of Results from Domain-Specific Text Analytics. In: Bornschlegl, M.X., Engel, F.C., Bond, R., Hemmje, M.L. (eds) Advanced Visual Interfaces. Supporting Big Data Applications. AVI-BDA 2016. Lecture Notes in Computer Science(), vol 10084. Springer, Cham. https://doi.org/10.1007/978-3-319-50070-6_6
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DOI: https://doi.org/10.1007/978-3-319-50070-6_6
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