Exploiting big data for customized online news recommendation system

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The news industry is undergoing major changes, with competition from non-traditional, international competitors negatively impacting both readership levels (pageviews) and the ad revenue associated to each pageview. The Globe and Mail is seeking a machine learning & big data solution to help them come out on top in this period of change. A system that offers personalized content recommendations to each user would help greatly. However, because their content library, akin to a product catalog at a retailer, changes dramatically every minute with the arrival of fresh news articles, traditional recommender systems would have a very hard time providing good recommendations of fresh articles. Traditional recommender systems also fail to consider popularity as a function of how much a piece of content was promoted, and the business consideration of the revenue driven by a piece of content. This project will combine big data and advanced algorithms to account for these considerations while driving personalized content recommendations.