How can you improve the results of one of the Web's most effective and respected recommendation engines? By pairing it up with another one.
That's exactly what the team at Hunch has done. The personalized recommendation service launched their browser-based Netflix Predictor today, which uses the company's "taste graph" to help determine what movie you should watch next.
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The films are made based no the preferences of over 500 million people on more than 200 million items. It also takes into account your existing Netflix ratings, and then asks you to rate a few more movies to fine-tune its recommendations.
The site does a pretty impressive job of suggesting what to watch. When I connected my Netflix account and started tinkering with the slider-based filters across the top, I found myself genuinely interested in checking out many of the films that popped up. The Web app lets you tweak the results by genre, release date, maturity rating and overall popularity.
The final product is a list of recommendations that is totally separate from Netflix's own native suggestions, as decent as those can be. In some ways, Hunch's are better, especially if you narrow things down using the filters.
You can also watch a trailer of each movie, read a summary and, if your interest is piqued, jump right to Netflix to start streaming, assuming the movie is available on demand.
Source: http://feedproxy.google.com/~r/readwriteweb/~3/QFCF4LWhxhQ/improve_netflix_movie_recommendations.php
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