TECHFLIX - MOVIE RECOMMENDER SYSTEM

App URL - Link

Objective:

• To build a recommender system which accepts the user preferences through an API and gives out three movie recommendations
• Note: Movies should be only films & Feature films in English language

Methods Used:

1. Web Scraping:

• Sources Considered: TMDB, IMDb, Box Office Mojo
• Data Collected: Top rated English movies are considered
• Scripting Language: Python
• Python Packages used:- Scraping: Beautiful Soup, Requests and Selenium. File Handling: Pandas
• API: TMDB API to fetch the movie data

How to create the TMDB API?

• Create TMDB account
• In profile section, select API request and provide contact information with application details
• Then use the API for getting data from TMDB website

How to use Selenium in Chrome?

• Open the Chrome browser and navigate to "Help -> About Google Chrome" and check the browser version
• Download the same version driver from this Link

Install the Packages

pip install requests
pip install selenium
pip install beautifulsoup4

2. Model Development:

Cosine Similarity Model: Recommender systems are an important class of machine learning algorithms offers “relevant” suggestions to users. There are 2 major types such as Content-based Filtering and Collaborative Filtering. Recommendation Systems work based on the similarity between either the content or the users who access the content. There are several ways to measure the similarity between two items. The recommendation systems use this similarity matrix to recommend the next most similar product to the user.

We will use the Cosine Similarity from Sklearn, as the metric to compute the similarity between two movies. Cosine similarity is a metric used to measure how similar two items are. Mathematically, it measures the cosine of the angle between two vectors projected in a multi-dimensional space. The output value ranges from 0–1.

0 means no similarity, where as 1 means that both the items are 100% similar.

Workflow:

How to Use:

• Select the Radio button as per the User wish
• Give any of the movies name from the list provided in the URL
• Click on the Search icon

Note:

• Recommend Movie will give 3 movies which is similar to the movie given as input

• Search Details will give the basic details of the movie

• Input: 1 Movie name

• Output: 3 Movies

Author:

• Mageshwari Singaravadivelou
• P. Saimounika