Contextual Word Spotting in Historical Manuscripts Using Markov Logic Networks. Fernández, D., Marinai, S., Lladόs, J., & Fornés, A. In Proceedings of the 2Nd International Workshop on Historical Document Imaging and Processing, of HIP '13, pages 36--43, Washington, District of Columbia, 2013. ACM. Paper doi abstract bibtex Natural languages can often be modelled by suitable grammars whose knowledge can improve the word spotting results. The implicit contextual information is even more useful when dealing with information that is intrinsically described as one collection of records. In this paper, we present one approach to word spotting which uses the contextual information of records to improve the results. The method relies on Markov Logic Networks to probabilistically model the relational organization of handwritten records. The performance has been evaluated on the Barcelona Marriages Dataset that contains structured handwritten records that summarize marriage information.
@inproceedings{ fernandez_contextual_2013,
address = {Washington, District of Columbia},
series = {{HIP} '13},
title = {Contextual Word Spotting in Historical Manuscripts Using Markov Logic Networks},
url = {http://doi.acm.org/10.1145/2501115.2501119},
doi = {10.1145/2501115.2501119},
abstract = {Natural languages can often be modelled by suitable grammars whose knowledge can improve the word spotting results. The implicit contextual information is even more useful when dealing with information that is intrinsically described as one collection of records. In this paper, we present one approach to word spotting which uses the contextual information of records to improve the results. The method relies on Markov Logic Networks to probabilistically model the relational organization of handwritten records. The performance has been evaluated on the Barcelona Marriages Dataset that contains structured handwritten records that summarize marriage information.},
booktitle = {Proceedings of the 2Nd International Workshop on Historical Document Imaging and Processing},
publisher = {{ACM}},
author = {Fernández, David and Marinai, Simone and Lladόs, Josep and Fornés, Alicia},
year = {2013},
keywords = {terminology_extraction, text_mining},
pages = {36--43}
}
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