Story Recommender

An abundance of choice presents users of many online and mobile platforms. Sorting through this to find desirable content is a challenge for users. To assist with this challenge and increase user interaction it is common to implement a recommendation system that can predict what kind of content a user will or will not be interested in. Wattpad uses such a recommendation system to connect users with stories. The research project will seek to identify relevant factors which can be used to improve the quality of recommendations given thereby building a stronger reader community. With millions of titles available to users, having a robust and trustworthy recommendation system is seen as crucial to Wattpad’s business.

Faculty Supervisor:

Dr. Frank Rudzicz


Craig Hagerman




Human physical performance and recreation


Media and communications


University of Toronto



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