An Intelligent Metadata Extraction Approach Based on Programming by Demonstration

Author:

Cui Binge,Zhang Jie

Publisher

Springer Berlin Heidelberg

Reference10 articles.

1. Seymore, K., McCallum, A., Rosenreid, R.: Learning hidden Markov model structure for information extraction. In: Califf, M.E., Freitag, D., Kushmerick, N., Muslea, I. (eds.) Proc. of the AAAI 1999 Workshop on Machine Learning for Information Extraction, pp. 37–42. MIT Press, Cambridge (1999)

2. McCallum, A., Freitag, D., Pereira, F.: Maximum entropy Markov models for information extraction and segmentation. In: Langley, P. (ed.) Proc. of the Int’l Conf. on Machine Learning (ICML 2000), pp. 591–598. Morgan Kaufmann Publishers, San Francisco (2000)

3. Lecture Notes in Artificial Intelligence;B. Chidlovskii,2001

4. Hitchcock, S., Carr, L., et al.: Developing services for open eprint archives: Globalisation, integration and the impact of links. In: Proc. of the 5th ACM Conf. on Digital Libraries (ACMDL 2000), pp. 143–151. ACM Press, New York (2000)

5. Klink, S., Dengel, A., Kieninger, T.: Rule-Based document structure understanding with a fuzzy combination of layout and textual features. Int’l Journal on Document Analysis and Recognition 4(1), 18–26 (2001)

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