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Master's Thesis von Christoph Erl

Last modified Nov 20, 2018

Semantic Text Matching of Company Policies and Regulatory Documents using Text Similarity Measures


Enterprise are enforced to comply to regulations by institutions such as governments. Large enterprise typically maintain individual policy documents. This arises the need to map the policies to different regulatory documents due to audits or for updates in either documents. Alyne is a startup that solves this problem with intermediate so-called control statements that maps to both: regulatory document paragraphs and enterprise policies paragraphs. The goal of this thesis is to investigate how far this mapping can be supported by the application of natural language processing and machine learning methods, in particular word embeddings.

Files and Subpages

Name Type Size Last Modification Last Editor
christoph_erl_final.pdf 9,60 MB 26.02.2018
christoph_erl_kickoff.pdf 2,69 MB 22.08.2017
christoph_erl_kickoff.pptx 21,52 MB 22.08.2017
christoph_erl_thesis.pdf 3,09 MB 26.02.2018