Netflix Recommendations - media opinions
11 Great Moments In Netflix Recommendationshttp://www.11points.com/Movies/11_Great_Moments_In_Netflix_Recommendations
http://www.huffingtonpost.com/news/netflix-recommendations/
http://www.huffingtonpost.com/2012/04/09/netflix-recommendations_n_1413179.html
Good Movies To Watch
http://agoodmovietowatch.com/netflix/
The Netflix Prize Winning Algorithm
http://www.netflixprize.com/assets/GrandPrize2009_BPC_BellKor.pdf
Five Best Movie Recommendation Services
http://lifehacker.com/5884202/five-best-movie-recommendation-servicesgood sites
ChickFlix
http://chickflix.net/
Rotten Tomatoe
http://www.rottentomatoes.com/
http://www.rottentomatoes.com/about/
http://www.rottentomatoes.com/about/
WHAT IS THE TOMATOMETER™?
The Tomatometer™ rating - based on the published opinions of hundreds of film and television critics - is a trusted measurement of movie and TV programming quality for millions of moviegoers.
The Tomatometer™ rating represents the percentage of professional critic reviews that are positive for a given film or television show.
Back in the days of the open theaters, when a play was particularly atrocious, the audience expressed their dissatisfaction by not only booing and hissing at the stage, but throwing whatever was at hand -- vegetables and fruits included.
A good review is denoted by a fresh red tomato. In order for a movie or TV show to receive an overall rating of Fresh, the reading on the Tomatometer for that movie must be at least 60%.
A bad review is denoted by a rotten green tomato splat (59% or less).
To receive a Certified Fresh rating a movie must have a steady Tomatometer rating of 75% or better. Movies opening in wide release need at least 80 reviews from Tomatometer Critics (including 5 Top Critics). Movies opening in limited release need at least 40 reviews from Tomatometer Critics (including 5 Top Critics). A TV show must have a Tomatometer Score of 75% or better with 20 or more reviews from Tomatometer Critics (including 5 Top Critics). If the Tomatometer score drops below 70%, then the movie or TV show loses its Certified Fresh status. In some cases, the Certified Fresh designation may be held at the discretion of the Rotten Tomatoes editorial team.
WHAT IS THE AUDIENCE SCORE?
The Audience rating, denoted by a popcorn bucket, is the percentage of all Flixster.com and RottenTomatoes.com users who have rated the movie or TV Show positively.
The full popcorn bucket means the movie received 3.5 stars or higher by Flixster and Rotten Tomatoes users.
The tipped over popcorn bucket means the movie received less than 3.5 stars by Flixster and Rotten Tomatoes users.
The plus sign will appear for movies that do not have audience ratings or reviews. The percentage you see associated with this icon is the percentage of users who added the movie to their Want-to-See list.
mediocre:
Criticker
http://www.criticker.com/
Jinni
http://www.jinni.com/
Criticker
http://www.criticker.com/
Jinni
http://www.jinni.com/
Metacritic
http://www.metacritic.com/
http://www.metacritic.com/
Netflix Recommendation Algorithm
[PDF] PushTrust: An Efficient Recommendation Algorithm by Leveraging Trust and Distrust Relations
R Forsati, I Barjasteh, F Masrour, AH Esfahanian… - Proceedings of the 9th ACM …, 2015
http://www.egr.msu.edu/waves/people/iman_files/RecSys_15_PushTrust_pres.pdfScaling Up Recommendation Services in Many Dimensions
B Németh - Proceedings of the 9th ACM Conference on …, 2015
... After successes in the Netflix Prize competition, the research team transformed into a company
providing recommendation and personalization solutions on a ... Currently he is focused on how
to apply state of the art recommendation algorithms in real world problems to help ...
providing recommendation and personalization solutions on a ... Currently he is focused on how
to apply state of the art recommendation algorithms in real world problems to help ...
Recommendation techniques in forensic data analysis: a new approach
M Quintana, S Uribe, F Sánchez, F Álvarez - … Prevention and Detection (ICDP-15), 6th …, 2015
... This technique was widely exploited at the Netflix prize [10], and it is ... provided by past cases, and
they are built over recommendation systems algorithms. ... methods inspire the “Clues
Recommendation Algorithm” while memory based collaborative filtering techniques are the ...
they are built over recommendation systems algorithms. ... methods inspire the “Clues
Recommendation Algorithm” while memory based collaborative filtering techniques are the ...
[PDF] POI Recommendation: Towards Fused Matrix Factorization with Geographical and Temporal Influences
JB Griesner, T Abdessalem, H Naacke - Proceedings of the 9th ACM Conference on …, 2015
... Matrix factorization techniques have demonstrated since the Netflix challenge [8] to be one of the
most accurate recommendation methods many ... Zhang et al. in [16] have proposed Collaborative
Location Activity Filtering (CLAF) algorithm for generic recommendation. ...
most accurate recommendation methods many ... Zhang et al. in [16] have proposed Collaborative
Location Activity Filtering (CLAF) algorithm for generic recommendation. ...
Content recommendation and service costs in swarming systems
D Munaro, C Delgado, DS Menasche - … (ICC), 2015 IEEE International Conference on, 2015
... Netflix alone accounts for up to 34% of North America's downloads during peak hours. ... Some
of the existing P2P systems already have some sort of content recommendation algorithm
embedded in the system [7]–[9], but none of these algorithms was implemented to influence ...
of the existing P2P systems already have some sort of content recommendation algorithm
embedded in the system [7]–[9], but none of these algorithms was implemented to influence ...
