Abstract
Molecular network structure to regulate plant seed development is very complex and to understand this from biomedical literature is a big challenge. Seed development is based on coordinated growth of different tissues, which are involved with complex genetics and environmental regulation. We develop a system for binary event extraction using statistical-, syntactic-, and dependency-based features. Experiments on the benchmark datasets of BioNLP-2016 SeeDev shared task show the recall, precision, and F-score values of 0.517, 0.399, and 0.451, respectively.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Kim, J.-D., Pyysalo, S., Tomoko, O., Robert, B., Ngan, N., Jun’ichi, T.: Overview of BioNLP shared task 2011. In: Proceedings of the BioNLP Shared Task 2011 Workshop, pp. 1–6 (2011)
Kim J.D., Ohta, T., Pyysalo, S., Kano, Y., Tsujii, J.: Overview of BioNLP09 shared task on event extraction. In: BioNLP 09: Proceedings of the Workshop on BioNLP, pp. 1–9 (2009)
Lishuang, L., Wang, Y., Huang, D.: Improving feature-based biomedical event extraction system by integrating argument information. In: Proceedings of the BioNLP Shared Task 2013 Workshop, pp. 109–115 (2013)
Bjorne, J., Salakoski, T.: Generalizing biomedical event extraction. In: Proceedings of BioNLP Shared Task 2011 Workshop (2011)
Chaix, E., Dubreucq, B., Fatihi, A., Valsamou, D., Bossy, R., Ba, M., Deléger, L., Zweigenbaum, P., Bessières, P., Lepiniec, L., Nedellec, C.: Overview of the regulatory network of plant seed development (seedev) task at the BioNLP shared task 2016. In: BioNLP (Shared Task), pp. 1–11. Association for Computational Linguistics (2016)
Deléger, L., Bossy, R., Chaix, E., Ba, M., Ferré, A., Bessières, P., Nedellec, C.: Overview of the bacteria biotope task at BioNLP shared task 2016. In: Proceedings of the 4th BioNLP Shared Task Workshop, BioNLP 2016, Berlin, Germany, pp. 12–22 (2016). https://doi.org/10.18653/v1/W16-3002. Accessed 13 Aug 2016
Li, H., Zhang, J., Wang, J., Lin, H., Yang, Z.: DUTIR in BioNLP-st 2016: utilizing convolutional network and distributed representation to extract complicate relations. In: Proceedings of the 4th BioNLP Shared Task Workshop, BioNLP 2016, Berlin, Germany, pp. 93–100 (2016). https://doi.org/10.18653/v1/W16-3012. Accessed 13 Aug 2016
Lamurias, A., Rodrigues, M.J., Clarke, L.A., Couto, F.M.: Extraction of regulatory events using kernel-based classifiers and distant supervision. In: Proceedings of the 4th BioNLP Shared Task Workshop, BioNLP 2016, Berlin, Germany, pp. 88–92 (2016). https://doi.org/10.18653/v1/W16-3011. Accessed 13 Aug 2016
Chandrasekarasastry, N.P., Khirbat, G., Verspoor, K., Cohn, T., Ramamohanarao, K.: SeeDev binary event extraction using svms and a rich feature set. In: BioNLP (Shared Task), pp. 82–87. Association for Computational Linguistics, Berlin (2016)
Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6, 181–197 (2002). (Velingrad)
Li, C., Rao, Z., Zhang, X.: Litway, discriminative extraction for different bio-events. In: BioNLP (Shared Task), pp. 32–41. Association for Computational Linguistics, Berlin (2016)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Majumder, A., Ekbal, A., Naskar, S.K. (2020). Feature Selection Using NSGA-II for Event Extraction on Genetic and Molecular Mechanisms Involved in Plant Seed Development. In: Das, A., Nayak, J., Naik, B., Pati, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. Advances in Intelligent Systems and Computing, vol 999. Springer, Singapore. https://doi.org/10.1007/978-981-13-9042-5_4
Download citation
DOI: https://doi.org/10.1007/978-981-13-9042-5_4
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9041-8
Online ISBN: 978-981-13-9042-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)