Datathon 2020 – NetInfo Article Recommender – Newbies

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The project aims to build a recommender system for the website called Vesti.bg. As the company runs to serve its huge customer base (as clear from the given data!) completely and for their best interests. And in order to do that it wants to recommend its users with articles that they should read next (based on mimicking their reading pattern). This is expected to save a lot of its users’ time in thinking. Also, with better and faster recommendations come people’s interest and that results in the company’s growth. The Company actually has a huge customer base. So, providing them with what they might like can really help it in making good money.

Datathon2020 – Article recommender case – provided by NetInfo

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For the past two decades we have been witnessing a never seen before access to information on one hand and at the same time the volume of the information has been exponentially growing. The rule: 90% of all data has been created in the past 2 years is still standing. This has lead to information overloading and the rise of recommendation systems. Guiding the user in this pool of data has proven to be critical for business success as we can see from YouTube, Amazon, Netflix and many others. Net Info has prepared another challenge: The next best article.