Abstract
There is a vast amount of scientific literature available from various resources such as the internet. Automating the extraction of knowledge from these resources is very helpful for biologists to easily access this information. This paper presents a system to extract the bacteria and their habitats, as well as the relations between them. We investigate to what extent current techniques are suited for this task and test a variety of models in this regard. We detect entities in a biological text and map the habitats into a given taxonomy. Our model uses a linear chain Conditional Random Field (CRF). For the prediction of relations between the entities, a model based on logistic regression is built. Designing a system upon these techniques, we explore several improvements for both the generation and selection of good candidates. One contribution to this lies in the extended flexibility of our ontology mapper that uses an advanced boundary detection and assigns the taxonomy elements to the detected habitats. Furthermore, we discover value in the combination of several distinct candidate generation rules. Using these techniques, we show results that are significantly improving upon the state of art for the BioNLP Bacteria Biotopes task.
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References
Bossy, R., Golik, W., Ratkovic, Z., Bessières, P., Nédellec, C.: BioNLP shared task 2013 - an overview of the bacteria biotope task. In: Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, Bulgaria. ACL, pp. 161–169 (2013)
Nédellec, C., Bossy, R., Kim, J.D., Kim, J.J., Ohta, T., Pyysalo, S., Zweigenbaum, P.: Overview of BioNLP shared task 2013. In: Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, Bulgaria. ACL, pp. 1–7 (2013)
Bossy, R., Jourde, J., Bessieres, P., van de Guchte, M., Nedellec, C.: BioNLP shared task 2011 - bacteria biotope. In: Proceedings of BioNLP Shared Task 2011 Workshop. ACL, pp. 56–64 (2011)
Bjorne, J., Salakoski, T.: Generalizing biomedical event extraction. In: Proceedings of BioNLP Shared Task 2011 Workshop. ACL (2011)
Nguyen, N.T.H., Tsuruoka, Y.: Extracting bacteria biotopes with semi-supervised named entity recognition and coreference resolution. In: Proceedings of BioNLP Shared Task 2011 Workshop. ACL (2011)
Ratkovic, Z., Golik, W., Warnier, P., Veber, P., Nedellec, C.: Task bacteria biotope-the Alvis system. In: Proceedings of BioNLP Shared Task 2011 Workshop. ACL (2011)
Bannour, S., Audibert, L., Soldano, H.: Ontology-based semantic annotation: an automatic hybrid rule-based method. In: Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, Bulgaria. ACL, pp. 139–143 (2013)
Claveau, V.: IRISA participation to BioNLP-ST 2013: lazy-learning and information retrieval for information extraction tasks. In: Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, Bulgaria. ACL, pp. 188–196 (2013)
Grouin, C.: Building a contrasting taxa extractor for relation identification from assertions: biological taxonomy & ontology phrase extraction system. In: Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, Bulgaria. ACL, pp. 144–152 (2013)
Karadeniz, I., Özgür, A.: Bacteria biotope detection, ontology-based normalization, and relation extraction using syntactic rules. In: Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, Bulgaria. ACL, pp. 170–177 (2013)
Björne, J., Salakoski, T.: TEES 2.1: automated annotation scheme learning in the BioNLP 2013 shared task. In: Proceedings of the BioNLP Shared Task 2013 Workshop, Sofia, Bulgaria. ACL, pp. 16–25 (2013)
Klein, D., Manning, C.D.: Fast exact inference with a factored model for natural language parsing. In: Advances in Neural Information Processing Systems (NIPS), vol. 15, pp. 3–10. MIT Press (2003)
Sutton, C., McCallum, A.: An Introduction to conditional random fields for relational learning. In: Getoor, L., Taskar, B. (eds.) Introduction to Statistical Relational Learning. MIT Press (2007)
Lei, J., Tang, B., Lu, X., Gao, K., Jiang, M., Xu, H.: A comprehensive study of named entity recognition in chinese clinical text. J. Am. Med. Inform. Assoc. 21, 808–814 (2014)
McCallum, A., Schultz, K., Singh, S.: FACTORIE: probabilistic programming via imperatively defined factor graphs. In: Neural Information Processing Systems (NIPS) (2009)
Porter, M.: An algorithm for suffix stripping. Program 14, 130–137 (1980)
Ramshaw, L.A., Marcus, M.P.: Text chunking using transformation-based learning. In: Proceedings of the 3rd ACL Workshop on Very Large Corpora, Cambridge, MA, USA, pp. 82–94 (1995)
Levenshtein, V.: Binary codes capable of correcting deletions, insertions and reversals. Sov. Phys. Dokl. 10, 707 (1966)
Kordjamshidi, P., Moens, M.F.: Global machine learning for spatial ontology population. J. Web Semant. 30, 3–21 (2015)
Kordjamshidi, P., Moens, M.F.: Designing constructive machine learning models based on generalized linear learning techniques. In: NIPS Workshop on Constructive Machine Learning (2013)
Kordjamshidi, P., Roth, D., Moens, M.F.: Structured learning for spatial information extraction from biomedical text: bacteria biotopes. BMC Bioinform. 16, 129 (2015)
Acknowledgements
This research is supported by grant 1U54GM114838 awarded by NIGMS through funds provided by the trans-NIH Big Data to Knowledge (BD2K) initiative (www.bd2k.nih.gov) and by Research Foundation Flanders (FWO) (grant G.0356.12). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Also we would like to thank the reviewers for their insightful comments and remarks.
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Kordjamshidi, P., Massa, W., Provoost, T., Moens, MF. (2015). Machine Reading for Extraction of Bacteria and Habitat Taxonomies. In: Fred, A., Gamboa, H., Elias, D. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2015. Communications in Computer and Information Science, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-27707-3_15
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