MA14KD (Movie Attract 14K Dataset) provides a set of 10 VISUAL features extracted from 14074 movie and tv series trailers. The movie IDs are in agreement with the movie IDs provided by another rating dataset that also contains movie genres and tags (see the description within the file). More details can be found in the following publication: Farshad B. Moghaddam, Mehdi Elahi, Reza Hosseini, Christoph Trattner, Marko Tkalcic, Predicting Movie Popularity and Ratings with Visual Features, IEEE SMAP’19, 9-10 June 2019, Larnaca, Cypru
We collected movie dataset from Internet Movie Database (IMDB) website for our experiments using an ...
Predicting movie success with machine learning algorithms has become a very popular research area. T...
Featured films are a multibillion-dollar industry. Online movie databases contain rich information a...
MA14KD (Movie Attract 14K Dataset) provides a set of 181 aggregated VISUAL features extracted from 1...
The MMTF-14K dataset provides a stable and extensive source for devising and evaluating movie recomm...
Trailers15k is a multi-label dataset containing 15,000 videos of movie trailers associated with 10 d...
Trailers12k is a movie trailer dataset comprised of 12,000 titles associated to ten genres. It disti...
This is a dataset comprising the technical data and the data from user reviews and score correspondi...
Transformed, cleaned dataset with reduced number of columns for all 45,000 movies listed in the full...
The world of movies contains enormous information and is worth digging for prediction and recommenda...
The dataset shows the films nominated for the Oscar for Best Picture since 1929. The dataset format ...
Abundance of movie data across the internet makes it an obvious candidate for machine learning and k...
This work will focus on the possibilities of data mining in film analysis and its use in predicting ...
International audienceThe ability of multimedia data to attract and keep people's interest for longe...
Dataset containing the highest rated movies in different categories by critics and users of Rotten T...
We collected movie dataset from Internet Movie Database (IMDB) website for our experiments using an ...
Predicting movie success with machine learning algorithms has become a very popular research area. T...
Featured films are a multibillion-dollar industry. Online movie databases contain rich information a...
MA14KD (Movie Attract 14K Dataset) provides a set of 181 aggregated VISUAL features extracted from 1...
The MMTF-14K dataset provides a stable and extensive source for devising and evaluating movie recomm...
Trailers15k is a multi-label dataset containing 15,000 videos of movie trailers associated with 10 d...
Trailers12k is a movie trailer dataset comprised of 12,000 titles associated to ten genres. It disti...
This is a dataset comprising the technical data and the data from user reviews and score correspondi...
Transformed, cleaned dataset with reduced number of columns for all 45,000 movies listed in the full...
The world of movies contains enormous information and is worth digging for prediction and recommenda...
The dataset shows the films nominated for the Oscar for Best Picture since 1929. The dataset format ...
Abundance of movie data across the internet makes it an obvious candidate for machine learning and k...
This work will focus on the possibilities of data mining in film analysis and its use in predicting ...
International audienceThe ability of multimedia data to attract and keep people's interest for longe...
Dataset containing the highest rated movies in different categories by critics and users of Rotten T...
We collected movie dataset from Internet Movie Database (IMDB) website for our experiments using an ...
Predicting movie success with machine learning algorithms has become a very popular research area. T...
Featured films are a multibillion-dollar industry. Online movie databases contain rich information a...