Divya worked on the Automated Legal Document Analytics (ALDA) project where she developed novel techniques to automate Cloud Service Level Agreements (SLAs) and Privacy Policies. Her research interests lie in Semantic Web and Text Analytics.
Divya successfully defended her Master’s thesis in April 2020.
MS Thesis title: Semantically Rich Framework to Automate Knowledge Extraction from Cloud Service Level Agreement
Committee: Dr. Karuna P Joshi (Chair), Dr. Tim Finin, Dr. Yelena Yesha
Consumers evaluate the performance of their cloud-based services by monitoring the Service Level Agreements (SLA) that list the service terms and metrics agreed with the service providers. Current Cloud SLAs are documents that require significant manual effort to parse and determine if providers meet the SLAs. Moreover, due to the lack of standardization, providers differ in the way they define the terms and metrics, making it more difficult to ensure continuous SLA monitoring. We have developed a novel framework to significantly automate the process of extracting knowledge embedded in cloud SLAs and representing it in a semantically rich Ontology. Our framework captures the key terms, standards, remedies for noncompliance and roles and responsibilities, in the form of deontic statements and their actors from cloud SLAs. It is built on major cloud SLAs and could be adapted to other domains as well. In this thesis `Semantically rich framework to automate knowledge extraction from cloud SLA’, we discuss the challenges in automating cloud services management and how we address these challenges with our framework.