Search results
Sep 23, 2019 · In this article will be presented some basic concepts in NLP and will be shown how to implement a simple model to compare similarity between movies summaries using the libraries scikit-learn and NLTK.
This project demonstrates how NLP techniques can be used to find similarities between movies based on their plot summaries. The use of a cluster algorithm and dendrogram provides a powerful tool for visualizing these similarities.
People also ask
How to find similarities between movies based on plot summaries?
Are movies with similar plot summaries clustered together?
How to build a content based movie recommender system?
Do movies within a genre share common base parameters?
Mar 17, 2024 · This Movie Recommendation System utilizes machine learning tools like pandas, numpy, and sklearn’s CountVectorizer and cosine_similarity to analyze user preferences and movie characteristics ...
Aug 4, 2023 · In this article, we’ll take a journey into a movie dataset using Python and the Pandas library. We’ll learn about preparing the data, creating visualizations, and even building a movie...
Aug 2, 2020 · Content-Based Movie Recommender System built using the cosine similarity scores. Table of Content. 1. Executive Summary. 2. Introduction. 3. Algorithm. 3.1. Content-Based filtering. 3.2....
- Ankit Raj
A machine learning model that can predict the genre of a movie based on its plot summary or other textual information. Used techniques like TF-IDF or word embeddings with classifiers such as Naive Bayes, Logistic Regression, or Support Vector Machines.
Mar 31, 2021 · In this notebook, we will quantify the similarity of movies based on their plot summaries available on IMDb and Wikipedia, then separate them into groups, also known as clusters. We'll create a dendrogram to represent how closely the movies are related to each other.
