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Viewer-Centered Intelligent Advertising System for Bell Media
In this project we will develop an intelligent advertisement system for Bell. First, we try to better understand each customer’s preferences through the content they watch. In order to achieve this, we extract context attributes from the media content that a customer watches. The context attribute can be extracted by analyzing the video, audio, and the metadata. We then correlate these attributes with different product groupings such as retail, travel, insurance, etc. We establish these correlations by running focus groups, crowd sourcing and using publicly available data on product group spending as of function of the demography. This level of personalization will not only improve user satisfaction but also provides Bell Media with a more effective advertising platform, ultimately leading to increased engagement and revenue.
Faculty Supervisor:
Shahram Shirani
Student:
Partner:
BCE Inc
Discipline:
Engineering
Sector:
Information and cultural industries
University:
McMaster University
Program:
Accelerate
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Mitacs is funded by the Government of Canada, the Government of Alberta, the Government of British Columbia, Research Manitoba, the Government of New Brunswick, the Government of Newfoundland and Labrador, the Government of Nova Scotia, the Government of Ontario, Innovation PEI, the Government of Quebec, the Government of Saskatchewan, and the Government of Yukon.