According to estimates, people on the internet spend about 40% of their time searching for content that interests them. Also, most content the user finds is out of place to the user's current context. We plan to create an application which cuts down this 40% to a minimum by suggesting content to users.
The content suggestion algorithm looks into three parameters of the target user.
- The user's interests
- Amount of spare time available to the user
- What the user is doing right now
Consider the scenario where the user is travelling. Based on his journey's ETA, and interests, we could possibly suggest content the user can consume.
Based on the user's content viewing history, We develop a statistical model of the user's self development index which is visualized for the user to see and improve upon.
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