Adaptive E-Commerce Recommendation Framework with Context-Aware Real-Time Personalization for Android Platforms

An adaptive e-commerce recommendation framework for Android that personalises results in real time from context.

An adaptive e-commerce recommendation framework for Android that personalises results in real time from context. This reference project walks through the whole job, from the problem and the design to the build and the evaluation, so that a developer can study how it works, run it and extend it.

It suits learners building mobile skills: screens and navigation, local and cloud data, notifications, and publishing a working app.

The main parts are real-time processing of incoming data, personalised recommendations ranked by relevance, an order and payment flow, secure sign-in, and clean screens for the main user journeys. The reference build uses scikit-learn, Apache Kafka, Razorpay, Kotlin, and Android SDK, with a clear project structure, setup instructions and sample data so that it can be run and extended.