Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019).

The Canadian insurance company La Capitale Assurances Générales has collected over time several massivex000D
datasets about their customers, insurance plans, and various insured items. They are now looking for ways ofx000D
efficiently combining these datasets together, enrich it with online data, and inferring new knowledge aboutx000D
customers from it, with the long-term goal of mining this data to learn more information about their customers'x000D
habits and lifestyles, in order to customize their insurance coverage to each individual customer's needs. In thex000D
original Engage grant, we designed learning algorithms to discover this knowledge from their data, andx000D
implemented a simple database to centralize the information into one source. In this follow-up Engage Plusx000D
grant, we will explore more advanced methods focusing on resolving the issue of the imbalanced class data inx000D
their dataset, an issue that was discovered during the work on the Engage grant, and we will improve thex000D
database system. The insurance industry is a multi-billion dollar industry, and the data management tools andx000D
knowledge discovery algorithms we will develop for La Capitale Assurances Générales will give Canadianx000D
companies an important edge in this competitive international marketplace.