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Using a sentiment analysis algorithm to recommend movies to the user by analyzing data containing movie descriptions, and unstructured metadata related to a movie, and using NLP techniques like topic modelling to build the dataset. Then queryaking in certain words or genres of movies, and using certain movies to recommend similar titles

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deepnz/netflix-movie-recommendations

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netflix-movie-recommendations

#In-progress merging previous project into new project

This app uses a cosine similarity algorithm: Cosine similarity is one of the metric to measure the text-similarity between two documents irrespective of their size in Natural language Processing. A word is represented into a vector form. The text documents are represented in n-dimensional vector space. Link-https://studymachinelearning.com/cosine-similarity-text-similarity-metric/#:~:text=Cosine%20similarity%20is%20one%20of,in%20n%2Ddimensional%20vector%20space.

to recommend movies to the user by analysing data containing movie descriptions, and unstructured data related to a movie, and using NLP techniques like topic modelling to build the dataset. Later the user can enter a query with a set of tags, or certain words/ genres of movies, and will output movie recommendations.

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Using a sentiment analysis algorithm to recommend movies to the user by analyzing data containing movie descriptions, and unstructured metadata related to a movie, and using NLP techniques like topic modelling to build the dataset. Then queryaking in certain words or genres of movies, and using certain movies to recommend similar titles

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