Artificial Intelligence for Information Governance: A Semantic Model to Automate the Appraisal and Description of Data, Information & Knowledge

Faced with the exponential growth of information sources, the instability of new digital forms and the convergence of data, content and records management systems, organizations are faced with increasing requirements to adopt an effective approach to exploit their information assets. Through the qualitative study of information inventories produced by Information Management experts, as well as automatic classification experiments, the research will develop a semantic model and its associated algorithms for the automatic classification of business records. The semantic model developed in this project will constitute a stepping-stone to automatically assigning metadata tags and retention periods on data, information and knowledge in various business contexts contributing to better corporate governance and accountability.

Intern: 
Tatiana Orel
Faculty Supervisor: 
Inge Alberts
Province: 
Ontario
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