For this use case, we used the large (20M) MovieLens dataset. This dataset contains a number of different files all related to movies and movie ratings. Here we will use files ratings.csv and ...
The Annals of the American Academy of Political and Social Science, Vol. 659, Toward Computational Social Science: Big Data in Digital Environments (May 2015), pp. 290-306 (17 pages) Theoretical and ...
Everyday decisions, from which products to buy, movies to watch and restaurants to try, are more and more being put in the hands of a new source: recommendation systems. Recommendation systems are ...
EACH year, thousands of films are released and tens of thousands of books published. A big city has thousands of restaurants. How does one deal with such abundance? Reading reviews of films, books and ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Using algorithms to make purchasing suggestions is big business. Netflix ...
In recent weeks I've given Digg.com a bit of coverage, albeit of the kind they wouldn't have enjoyed. But actually I love the concept of digg.com and I still think it has a lot of potential, as long ...
An executive from Chinese social media giant ByteDance played down the role of its content-recommendation algorithms in creating so-called filter bubbles, as the company faces intense scrutiny from ...
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