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Feature Selection for Document Flow Segmentation
Overview
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Citations
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Cited by 7
Research works printed but not linked: 19
- kanerva, 2000, Random indexing of text samples for latent semantic analysis, Proceedings of the Cognitive Science Society, 1
- 10.1109/DAS.2016.21 · DOI · Paper page
- kumar, 2012, Learning document structure for retrieval and classification, Pattern Recognition (ICPR) 2012 21st International Conference on, 1558
- lewis, 1994, A comparison of two learning algorithms for text categorization, Third Annual Symposium on Document Analysis and Information Retrieval, 33, 81
- 10.1007/s10032-014-0225-8 · DOI · Paper page
- 10.1109/ICDAR.2003.1227795 · DOI
- shin, 2001, Classification of document pages using structure-based features, International Journal on Document Analysis and Recognition, 3, 232, 10.1007/PL00013566 · DOI
- yang, 2009, Extended vsm for xml document classification using frequent subtrees, Proc 5th Int Workshop Initiative Evaluation XML Retrieval, 441
- 10.1145/312624.312647 · DOI
- yang, 1997, A comparative study on feature selection in text categorization, ICML, 97, 412
- 10.1109/ICDAR.1995.601965 · DOI
- 10.1109/ICDAR.1993.395776 · DOI
- gordo, 2010, A bag-of-pages approach to unordered multipage document classification, Pattern Recognition (ICPR), 1920
- 10.1007/s11554-011-0227-4 · DOI
- 10.1142/S0218213094000121 · DOI
- 10.1109/TAI.1993.633991 · DOI
- collins-thompson, 2002, A clustering-based algorithm for automatic document separation, SIGIR 2002 Workshop on Information Retrieval and OCR From Converting Content to Grasping Meaning Tampere Finland
- belaid, 2013, Handwritten and Printed Text Separation in Real Document
- 10.1109/ICPR.1998.711385 · DOI
Metadata
- Authors
- Hamdi, A., Coustaty, M., Joseph, A., d'Andecy, V. P., Doucet, A., & Ogier, J.-M.
- Venue
- 2018 13th IAPR International Workshop on Document Analysis Systems (DAS)
- Publisher
- IEEE
- Published
- 2018-04
- Pages
- 245-250
- Cited by
- 7
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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- CoChat. (2026). Citation check: Feature Selection for Document Flow Segmentation. https://app.cochat.ai/papers/10.1109/das.2018.66
- The paper
- Hamdi, A., Coustaty, M., Joseph, A., d'Andecy, V. P., Doucet, A., & Ogier, J.-M. (2018). Feature Selection for Document Flow Segmentation. 2018 13th IAPR International Workshop on Document Analysis Systems (DAS). https://doi.org/10.1109/das.2018.66
