Content-based Recommender Using Natural Language Processing (NLP) - KDnuggets


When we provide ratings for products and services on the internet, all the preferences we express and data we share (explicitly or not), are used to generate recommendations by recommender systems. The most common examples are that of Amazon, Google and Netflix. In this article, I have combined movie attributes such as genre, plot, director and main actors to calculate its cosine similarity with another movie. The dataset is IMDB top 250 English movies downloaded from Exploring the dataset, there are 250 movies (rows) and 38 attributes (columns).

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