Diego A. Burgos

Also published as: Diego Burgos


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NLP-CIC-WFU at SocialDisNER: Disease Mention Extraction in Spanish Tweets Using Transfer Learning and Search by Propagation
Antonio Tamayo | Alexander Gelbukh | Diego Burgos
Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop & Shared Task

Named entity recognition (e.g., disease mention extraction) is one of the most relevant tasks for data mining in the medical field. Although it is a well-known challenge, the bulk of the efforts to tackle this task have been made using clinical texts commonly written in English. In this work, we present our contribution to the SocialDisNER competition, which consists of a transfer learning approach to extracting disease mentions in a corpus from Twitter written in Spanish. We fine-tuned a model based on mBERT and applied post-processing using regular expressions to propagate the entities identified by the model and enhance disease mention extraction. Our system achieved a competitive strict F1 of 0.851 on the testing data set.


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Exploring MWEs for Knowledge Acquisition from Corporate Technical Documents
Bell Manrique Losada | Carlos M. Zapata Jaramillo | Diego A. Burgos
Proceedings of the 9th Workshop on Multiword Expressions


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Combining CBIR and NLP for Multilingual Terminology Alignment and Cross-Language Image Indexing
Diego Burgos
Proceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas