KPMG Research Project

Continuous Curation of a Knowledge Base System for Data Auditing

Dates: Sept 2018 – Aug 2021

The main goal of this project is to create an end-to-end framework to assist domain experts in creating and curating a knowledge base system from auditing documents. We are building a hybrid system that uses the machine to scale over the large dataset, and the domain experts to teach the algorithms how to solve the hard cases. To involve audit specialists without coding skills or CS background, the interaction between the system and the domain experts will rely on questions over the data. Our focus is on developing efficient and effective algorithms that minimizes the user effort while guaranteeing the high quality of the data.

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Paolo Papotti
Associate Professor of Computer Science

His research focuses on the broad area of scalable data management, with a focus on data and information quality.