Welcome to the Recommendation Engine Accelerator!

About Recommendation Engine

An engine developed on R Studio and Shiny package generating Smart Recommendations based on historical patterns, behaviors and preferences.
The engine can prescribe a product, a service, a bundle of packages, a set of customers/rules to increase conversion rates
for your organization.

Features
1.) This Accelerator takes Recommendation Algorithms files run in backend and shows the output for it
2.) Uses Collaborative based Filtering (User Based or Item Based) to provide User or Item based Feature matrix
3.) Uses Content based Filtering (historical preferences) to provide Item based Feature matrix
4.) Uses Market Basket Analysis to group items that could be sold togetherUses Market Basket Analysis to group items that could be sold together

Test the App

To test the app, you can simply Select a pre-loaded dataset
After which you can select the algorithm (Currently Collaborative Filtering is available).

Application Areas

Ecommerce
Item recommendations based on transaction history and baskets

Entertainment
Movie, video and music Suggestions based on views and ratings

Other Services
Hotel Package recommendations, travel itineraries & Food combos based on customer preferences

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Genre Wise Recommendations

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Past Purchases by the User

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Similar Users Network

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