Semantic analysis of contractual agreements to support end-user interpretation

The ubiquitous availability of the Internet results in a huge number of apps, software and online services with accompanying contractual agreements in the form of `terms of use' and `privacy policy'. Although everyone is exposed to such consent forms, the majority tend to ignore them due to their length and complexity. In this thesis, we focus on interpretation of contractual agreements for the benefit of end-users. By applying text mining and semantic technologies, we develop an approach that extracts important information and retrieves helpful links and resources for the better comprehension. Our approach is based on ontology-based information extraction and machine learning and delivers the unpleasant consent form in a user friendly and visualized format. The evaluation shows that although semi-automatic approaches lead to information loss, they save time and effort by producing instant results and facilitate the end-users' understanding of legal texts.