Abstract
Despite tremendous advances in computer software and hardware, certain key aspects of experimental research in document analysis, and pattern recognition in general, have not changed much over the past 50 years. This paper describes a vision of the future where community-created and managed resources make possible fundamental changes in the way science is conducted in such fields. We also discuss current developments that are helping to lead us in this direction.
This work is a collaborative effort hosted by the Computer Science and Engineering Department at Lehigh University and funded by a Congressional appropriation administered through DARPA IPTO via Raytheon BBN Technologies.
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References
Boulicaut, J.F., Masson, C.: Data mining query languages. In: Maimon, O., Rokach, L. (eds.) Data Mining and Knowledge Discovery Handbook, pp. 655–664. Springer, US (2010), doi:10.1007/978-0-387-09823-4_33
Clavelli, A., Karatzas, D., Lladós, J.: A framework for the assessment of text extraction algorithms on complex colour images. In: DAS 2010: Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, pp. 19–26. ACM, New York (2010)
Dotsika, F.: Uniting formal and informal descriptive power: Reconciling ontologies with folksonomies. International Journal of Information Management 29(5), 407–415 (2009)
Eco, U.: The limits of interpretation. Indiana University Press (1990)
Feigenbaum, L., Herman, I., Hongsermeier, T., Neumann, E., Stephens, S.: The semantic web in action. Scientific American (December 2007)
Hu, J., Kashi, R., Lopresti, D., Nagy, G., Wilfong, G.: Why table ground-truthing is hard. In: 6th International Conference on Document Analysis and Recognition, pp. 129–133. IEEE Computer Society, Los Alamitos (2001)
Kim, H.L., Decker, S., Breslin, J.G.: Representing and sharing folksonomies with semantics. Journal of Information Science 36(1), 57–72 (2010)
Lamiroy, B., Lopresti, D.: A platform for storing, visualizing, and interpreting collections of noisy documents. In: Fourth Workshop on Analytics for Noisy Unstructured Text Data - AND 2010. ACM International Conference Proceeding Series, IAPR. ACM, Toronto (2010)
Lamiroy, B., Lopresti, D., Korth, H., Jeff, H.: How carefully designed open resource sharing can help and expand document analysis research. In: Agam, G., Viard-Gaudin, C. (eds.) Document Recognition and Retrieval XVIII. SPIE Proceedings, vol. 7874. SPIE, San Francisco (2011)
Lopresti, D., Nagy, G., Smith, E.B.: Document analysis issues in reading optical scan ballots. In: DAS 2010: Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, pp. 105–112. ACM, New York (2010)
Nagy, G.: Document systems analysis: Testing, testing, testing. In: Doerman, D., Govindaraju, V., Lopresti, D., Natarajan, P. (eds.) DAS 2010, Proceedings of the Ninth IAPR International Workshop on Document Analysis Systems. p. 1 (2010), http://cubs.buffalo.edu/DAS2010/GN_testing_DAS_10.pdf (downloded November 10, 2010)
Raub, W., Weesie, J.: Reputation and efficiency in social interactions: An example of network effects. American Journal of Sociology 96(3), 626–654 (1990)
Sabater, J., Sierra, C.: Review on computational trust and reputation models. Artificial Intelligence Review 24(1), 33–60 (2005)
Smith, E.H.B.: An analysis of binarization ground truthing. In: DAS 2010: Proceedings of the 8th IAPR International Workshop on Document Analysis Systems, pp. 27–34. ACM, New York (2010)
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Lopresti, D., Lamiroy, B. (2011). Document Analysis Research in the Year 2021. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds) Modern Approaches in Applied Intelligence. IEA/AIE 2011. Lecture Notes in Computer Science(), vol 6703. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21822-4_27
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DOI: https://doi.org/10.1007/978-3-642-21822-4_27
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