2. REPORT (RECOMMENDATION ALGORITHMS) YouTube is an American online video sharing platform launched in February 2005. It is the second most visited website worldwide, with more than one billion monthly users who collectively watch more than one billion hours of videos each day. As of May 2019, videos were being uploaded at a rate of more than 500 hours of content per minute. Video categories on YouTube include music videos, video clips, news, short films, feature films, documentaries, movie trailers, teasers, live streams and more. Most content is generated by individuals. YouTube has had a substantial social impact, influencing popular culture and Internet trends. It has been criticised for facilitating the spread of misinformation, copyright issues and endangering child safety and wellbeing. Let us assume that you are working for a consultancy company called Plymouth IT Consultants, which has been hired by YouTube to redesign its recommendation system. As Chief Data Officer at Plymouth IT Consultants, you have been asked to propose a new recommendation algorithm based, entirely, on graph databases. Using the material introduced in COMP5001, you will write a 3000- word report discussing your proposed recommendation algorithm. Essentially, you must explain how the algorithm works and justify why this is the best way to do it. If you propose a recommendation algorithm based on influence scoring, you must explain—among other considerations—which formula you will use to calculate the influence score. It may also be the case that you propose a combination of the algorithms taught in COMP5001. While this seems a promising alternative, you will have to clarify how exactly you attempt to combine the algorithms— which one you will apply first, how much “importance” will be assigned to each algorithm, and what is the actual advantage of the combination. Note that your report should focus, exclusively, on the YouTube recommendation algorithm. Evidently, YouTube has different