Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Relational Markov models and their application to adaptive web navigation
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Word Spotting: A New Approach to Indexing Handwriting
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Machine Learning
Searching Off-line Arabic Documents
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Entity Resolution with Markov Logic
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Word spotting for historical documents
International Journal on Document Analysis and Recognition
Dynamic Handwritten Keyword Spotting Based on the NSHP-HMM
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
Locality Sensitive Pseudo-Code for Document Images
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
Handwritten word-spotting using hidden Markov models and universal vocabularies
Pattern Recognition
Segmentation-free Word Spotting in Historical Printed Documents
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
HMM-based Word Spotting in Handwritten Documents Using Subword Models
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Text retrieval from early printed books
International Journal on Document Analysis and Recognition - Special issue on noisy text analytics
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method
ICDAR '11 Proceedings of the 2011 International Conference on Document Analysis and Recognition
Loglinear models for first-order probabilistic reasoning
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
A Novel Word Spotting Method Based on Recurrent Neural Networks
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey on statistical relational learning
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Context models and out-of-context objects
Pattern Recognition Letters
Contextual semantic processing for a spanish dialogue system using markov logic
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
A Model-Based Sequence Similarity with Application to Handwritten Word Spotting
IEEE Transactions on Pattern Analysis and Machine Intelligence
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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.