Suppose you’re a data scientist consultant, and one of your clients is Goodreads. Goodreads is a social cataloging website that allows individuals to freely search its database ofbooks, annotations, and reviews. Users can sign up and register books to generate librarycatalogs and reading lists. With a model in place, the company recommends books to new andexisting uses. They want you to work on improving their model. How would you approach thisproblem? Based on your understanding of how recommender systems are built using acombination of how content and collaborative filtering is used, what five features would you rankas most important for this task? Justify why you would need every data point/feature using theconcepts from the theory of recommender systems. (Hint:!)What five features? What is your take on this?

a  social news website  is an  internet  website  that features  user-posted stories. such stories are ranked based on popularity, as voted on by other users of the site or by website administrators. users typically comment online on the news posts and these comments may also be ranked in popularity. since their emergence with the birth of  web 2.0, social news sites have been used to link many types of information, including news, humor, support, and discussion. all such websites allow the users to submit content and each site differs in how the content is moderated. on the  slashdot  and  fark  websites,  administrators  decide which articles are selected for the front page. on  reddit  and  digg, the articles that get the most votes from the community of users will make it to the front page. many social news websites also feature an online comment system, where users discuss the issues raised in an article. some of these sites have also applied their voting system to the comments, so that the most popular comments are displayed first. some social news websites also have a  social networking  function, in that users can set up a user profile and follow other users' online activity on the website.