Abstract
The global legislation system is being actively updated, especially after the financial crisis of 2007–2008. This results in a significant amount of work load for the different industries, in order to cope up with the volume, velocity, variety, and complexity of the regulations in order to be compliant. So far, this is mainly being handled manually by the regulatory experts in the industries. In this paper, we explore the space of providing automatic assistance to experts in compliance verification pipeline. This work specifically focuses on performing automatic semantic annotations of the regulatory documents with a set of predefined categories. This is achieved by using text classification approaches using linguistically motivated features.
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References
Asooja, K., Bordea, G., Vulcu, G., O’Brien, L., Espinoza, A., Abi-Lahoud, E., Buitelaar, P., Butler, T.: Semantic annotation of finance regulatory text using multilabel classification (2015)
Baker, C.F., Fillmore, C.J., Lowe, J.B.: The berkeley framenet project. In: Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics - vol. 1, ACL 1998, Stroudsburg, PA, USA, pp. 86–90. Association for Computational Linguistics (1998)
Buabuchachart, A., Metcalf, K., Charness, N., Morgenstern, L.: Classification of regulatory paragraphs by discourse structure, reference structure, and regulation type (2013)
Chen, D., Schneider, N., Das, D., Smith, N.A.: Semafor: Frame argument resolution with log-linear models. In: Proceedings of the 5th International Workshop on Semantic Evaluation, pp. 264–267. Association for Computational Linguistics (2010)
Das, D., Chen, D., Martins, A.F., Schneider, N., Smith, N.A.: Frame-semantic parsing. Comput. Linguist. 40(1), 9–56 (2014)
Elgammal, A., Butler, T.: Towards a framework for semantically-enabled compliance management in fiancial services. In: Toumani, F., et al. (eds.) ICSOC 2014. LNCS, vol. 8954, pp. 171–184. Springer, Heidelberg (2015)
Francesconi, E., Passerini, A.: Automatic classification of provisions in legislative texts. Artif. Intell. Law 15(1), 1–17 (2007)
Morgenstern, L.: Toward automated international law compliance monitoring (tailcm). Technical report, Intelligence Advanced Research Projects Activity (IARPA) (2014)
Read, J., Pfahringer, B., Holmes, G., Frank, E.: Classifier chains for multi-label classification. Mach. Learn. 85(3), 333–359 (2011)
Acknowledgement
This work has been funded in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (INSIGHT) and by Enterprise Ireland (EI) as part of the project Financial Services Governance, Risk and Compliance Technology Centre (GRCTC), University College Cork, Ireland.
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Asooja, K., Bordea, G., Buitelaar, P. (2016). Using Semantic Frames for Automatic Annotation of Regulatory Texts. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2016. Lecture Notes in Computer Science(), vol 9612. Springer, Cham. https://doi.org/10.1007/978-3-319-41754-7_38
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DOI: https://doi.org/10.1007/978-3-319-41754-7_38
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