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dc.contributor.authorCamilleri, John J.
dc.date.accessioned2017-10-11T07:51:32Z
dc.date.available2017-10-11T07:51:32Z
dc.date.issued2017-10-11
dc.identifier.isbn978-91-982237-4-3
dc.identifier.urihttp://hdl.handle.net/2077/53815
dc.description.abstractWhether we are aware of it or not, our digital lives are governed by contracts of various kinds, such as privacy policies, software licenses, service agreements, and regulations. At their essence, normative documents like these dictate the permissions, obligations, and prohibitions of two or more parties entering into an agreement, including the penalties which must be paid when someone breaks the rules. Such documents are often lengthy and hard to understand, and most people tend to agree to these legally binding contracts without ever reading them. Our goal is to create tools which can take a natural language document as input and allow an end user to easily ask questions about its implications, getting back meaningful answers in natural language within a reasonable amount of time. We do this by bringing formal methods to the analysis of normative texts, investigating how they can be effectively modelled and the kinds of automatic processing that these models enable. This thesis includes six research papers by the author which cover the various aspects of this approach: entity recognition and modality extraction from natural language, controlled natural languages and visual diagrams as interfaces for modelling, logical formalisms which can be used for contract representation, and analysis via syntactic filtering, trace evaluation, random testing, and model checking. These components are then combined into a prototype tool for end users, allowing for end-to-end analysis of normative texts in natural language.sv
dc.language.isoengsv
dc.relation.ispartofseries145Dsv
dc.relation.haspartI. John J. Camilleri and Gerardo Schneider. “Modelling and Analysis of Normative Documents”. In: Logical and Algebraic Methods in Programming 91 (2017), pp. 33–59.::doi::10.1016/j.jlamp.2017.05.002sv
dc.relation.haspartII. Runa Gulliksson and John J. Camilleri. “A Domain-Specific Language for Normative Texts with Timing Constraints”. In: International Symposium on Temporal Representation and Reasoning (TIME 2016). IEEE, 2016, pp. 60–69.::doi::10.1109/TIME.2016.14sv
dc.relation.haspartIII. Krasimir Angelov, John J. Camilleri, and Gerardo Schneider. “A Framework for Conflict Analysis of Normative Texts Written in Controlled Natural Language”. In: Logic and Algebraic Programming 82.5-7 (2013), pp. 216–240.::doi::10.1016/j.jlap.2013.03.002sv
dc.relation.haspartIV. John J. Camilleri, Gabriele Paganelli, and Gerardo Schneider. “A CNL for Contract-Oriented Diagrams”. In: International Workshop on Controlled Natural Language (CNL 2014). Vol. 8625. Lecture Notes in Computer Science. Springer, 2014, pp. 135–146.::doi::10.1007/978-3-319-10223-8_13sv
dc.relation.haspartV. John J. Camilleri, Normunds Grūzītis, and Gerardo Schneider. “Extracting Formal Models from Normative Texts”. In: International Conference on Applications of Natural Language to Information Systems (NLDB 2016). Vol. 9612. Lecture Notes in Computer Science. Springer, 2016, pp. 403–408.::doi::10.1007/978-3-319-41754-7_40sv
dc.relation.haspartVI. John J. Camilleri, Mohammad Reza Haghshenas, and Gerardo Schneider. “A Web-Based Tool for Analysing Normative Documents in English”. 2017. arXiv: 1707.03997 [cs.CL] https://arxiv.org/abs/1707.03997sv
dc.subjectnormative textssv
dc.subjectcontract analysissv
dc.subjectcontrolled natural languagesv
dc.subjectmodel checkingsv
dc.titleContracts and Computation — Formal modelling and analysis for normative natural languagesv
dc.typeText
dc.type.svepDoctoral thesis
dc.gup.mailjohn.j.camilleri@cse.gu.sesv
dc.type.degreeDoctor of Philosophysv
dc.gup.originGöteborgs universitet. IT-fakultetensv
dc.gup.departmentDepartment of Computer Science and Engineering ; Institutionen för data- och informationstekniksv
dc.citation.doiITF
dc.gup.defenceplaceOnsdagen den 1 november 2017, kl. 10.00, HC3, Hörsalsvägen 14sv
dc.gup.defencedate2017-11-01


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