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IMDb (an initialism for Internet Movie Database) [ 2 ] is an online database of information related to films, television series, podcasts, home videos, video games, and streaming content online – including cast, production crew and personal biographies, plot summaries, trivia, ratings, and fan and critical reviews.
The datasets, which have each been cited more than 100,000 times, include text-based ones from newsgroups, Amazon and IMDb. Errors emerged from issues like Amazon product reviews being mislabeled ...
These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high ...
The two researchers de-anonymized some of the data by comparing it with non-anonymous IMDb (Internet Movie Database) users' movie ratings. Very little information from the database, it was found, was needed to identify the subscriber. [3] In the resulting research paper, there were startling revelations of how easy it is to re-identify Netflix ...
The Internet Movie Database IMDB represents one of the largest internet sources for movies/actors data, and it is where most of the datasets are collected to study the collaboration network of co-star actors. IMDB facilitates the ability to collect data for very specific and variable types of network.
MovieLens is a web-based recommender system and virtual community that recommends movies for its users to watch, based on their film preferences using collaborative filtering of members' movie ratings and movie reviews. It contains about 11 million ratings for about 8500 movies. [1] MovieLens was created in 1997 by GroupLens Research, a ...
AllMusic. Music information and reviews. ~20,000,000 [7] ~2,200,000 [7] Song samples only. Discogs. • Database: user-generated cross-referenced database of physical & digital releases, artists, and labels. With catalogue numbers, codes, and other markings taken directly from each release.
The Netflix Prize was an open competition for the best collaborative filtering algorithm to predict user ratings for films, based on previous ratings without any other information about the users or films, i.e. without the users being identified except by numbers assigned for the contest. The competition was held by Netflix, a video streaming ...