Time Series Prediction on Movie Rating Data
DOI:
https://doi.org/10.61841/sdsfhm55Keywords:
time series, movie, ratings, Movielens, fbprophetAbstract
Time series is known as a method to make predictions based on a series of data. It has some benefit in a lot of research domains, including marketing, sports, and education. A movie is a popular entertainment part that has a great number of fans. People choose movies with specific genres and share some similar interests. This research uses the Movielens dataset as input for time series processing. This dataset contains historical data about users, ratings, and datetime. This research implements timeseries on the Movielens dataset to make predictions on rating values by using the fbprophet library. The experiment shows that the algorithm can predict the future rating, which approximately will be chosen by users. Then the objective of this research is to create recommendations based on predicted ratings for whatever movie is the next choice.
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