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 ...
With increasing amounts of information available, modeling and predicting user preferences—for books or articles, for example—are becoming more important. We present a collaborative filtering model, ...
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 ...
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 ...
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 ...
Amazon worldwide consumer CEO Jeff Wilke gave attendees of the company’s Re:Mars conference a look behind the curtain of content recommendation for Prime Video Wednesday, explaining how the company ...
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