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Machine Learning vs Deterministic Rule-Based System for Document Stream Segmentation
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Cited by 6
Research works printed but not linked: 22
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- 10.1109/DAS.2016.21 · DOI · Paper page
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Metadata
- Authors
- Hamdi, A., Voerman, J., Coustaty, M., Joseph, A., d'Andecy, V. P., & Ogier, J.-M.
- Venue
- 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)
- Publisher
- IEEE
- Published
- 2017-11
- Pages
- 77-82
- Cited by
- 6
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- The paper
- Hamdi, A., Voerman, J., Coustaty, M., Joseph, A., d'Andecy, V. P., & Ogier, J.-M. (2017). Machine Learning vs Deterministic Rule-Based System for Document Stream Segmentation. 2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR). https://doi.org/10.1109/icdar.2017.332
