R. Hashemi, C. W. Ford, T. Vamprooyan, and J. Talburt, Extraction of features with unstructured representation from html documents, IADIS International Conference on WWW/Internet, pp.47-53, 2002.

O. O. Isaac, T. John, and R. , A data-intensive approach to named entity recognition combining contextual and intrinsic indicators, International Journal of Business Intelligence Research, vol.3, issue.1, pp.55-71, 2012.

V. T. Chakaravarthy, H. Gupta, P. Roy, and M. Mohania, Efficiently linking text documents with relevant structured information, Proceedings of the International Conference on Very Large Data Bases, pp.667-678, 2006.

N. Kooli and A. Bela¨?dbela¨?d, Semantic Label and Structure Model based Approach for Entity Recognition in Database Context, 2015 13th International Conference on Document Analysis and Recognition (ICDAR), pp.301-305, 2015.
DOI : 10.1109/ICDAR.2015.7333772
URL : https://hal.archives-ouvertes.fr/hal-01191425

J. Liang and D. S. Doermann, Logical Labeling of Document Images Using Layout Graph Matching with Adaptive Learning, Proceedings of Document Analysis Systems, pp.224-235, 2002.
DOI : 10.1007/3-540-45869-7_26

K. C. Santosh, g-DICE: graph mining-based document information content exploitation, International Journal on Document Analysis and Recognition (IJDAR), vol.7, issue.1, pp.337-355, 2015.
DOI : 10.1007/s10032-015-0253-z

N. Kooli and A. Bela¨?dbela¨?d, Entity Matching in OCRed Documents with Redundant Databases, Proceedings of the International Conference on Pattern Recognition Applications and Methods, pp.165-172, 2015.
DOI : 10.5220/0005177301650172
URL : https://hal.archives-ouvertes.fr/hal-01144641

D. Conte, P. Foggia, C. Sansone, and M. Vento, THIRTY YEARS OF GRAPH MATCHING IN PATTERN RECOGNITION, International Journal of Pattern Recognition and Artificial Intelligence, vol.31, issue.03, pp.265-298, 2004.
DOI : 10.1109/21.57275
URL : https://hal.archives-ouvertes.fr/hal-01408706

E. R. Hancock and R. C. Wilson, Pattern analysis with graphs: Parallel work at Bern and York, Pattern Recognition Letters, vol.33, issue.7, pp.833-841, 2012.
DOI : 10.1016/j.patrec.2011.08.012

P. Foggia, G. Percannella, and M. Vento, GRAPH MATCHING AND LEARNING IN PATTERN RECOGNITION IN THE LAST 10 YEARS, International Journal of Pattern Recognition and Artificial Intelligence, vol.15, issue.01, 2014.
DOI : 10.1109/TPAMI.2008.245

A. Sanfeliu and K. Fu, A distance measure between attributed relational graphs for pattern recognition, IEEE Transactions on Systems, Man, and Cybernetics, vol.13, issue.3, pp.353-362, 1983.
DOI : 10.1109/TSMC.1983.6313167

P. L. Bodic, P. Héroux, S. Adam, and Y. Lecourtier, An integer linear program for substitution-tolerant subgraph isomorphism and its use for symbol spotting in technical drawings, Pattern Recognition, vol.45, issue.12, pp.4214-4224, 2012.
DOI : 10.1016/j.patcog.2012.05.022
URL : https://hal.archives-ouvertes.fr/hal-00726076

N. Kooli, A. Belaid, A. Joseph, and V. P. , Entity Local Structure Graph Matching for Mislabeling Correction, 2016 12th IAPR Workshop on Document Analysis Systems (DAS), pp.257-262, 2016.
DOI : 10.1109/DAS.2016.36
URL : https://hal.archives-ouvertes.fr/hal-01304257

A. Wong, M. You, and S. Chan, An algorithm for graph optimal monomorphism, IEEE Transactions on Systems, Man, and Cybernetics, vol.20, issue.3, pp.628-638, 1990.
DOI : 10.1109/21.57275

P. Vijaya, M. N. Murty, and D. Subramanian, Leaders???Subleaders: An efficient hierarchical clustering algorithm for large data sets, Pattern Recognition Letters, vol.25, issue.4, pp.505-513, 2004.
DOI : 10.1016/j.patrec.2003.12.013

H. Bunke, P. Foggia, C. Guidobaldi, and M. Vento, Graph Clustering Using the Weighted Minimum Common Supergraph, Proceedings of the IAPR International Conference on Graph Based Representations in Pattern Recognition, pp.235-246, 2003.
DOI : 10.1007/3-540-45028-9_21