The objective of this bachelor thesis was the research, development and implementation of a social network based commercial application’s prototype, in association with Artklikk Kft. for their reasearch & development project. The application supports content-based filtering of products by mapping user preferences, striving to gain more precision in product recommendations.
This sample application was created to recommend perfumes to users, but the long term goal is to build an experimental system which then can be applied to a wide variety of products and services in the future.
During the development process certain possible future scenarios had to be considered, such as the potentially rapid growth in the number of users, in case of a sudden rise in the application’s popularity. For this reason the focus was aimed at using virtual, cloud based application server services, such as Google’s App Engine.
The thesis gives an overview of all the required elements needed for the development of the back-end service, like the data model, the relevance-measuring algorithms and the RESTful architecture based client-server communications.
This document also deals with the development and functional testing of the App Engine back-end and Android-based client prototypes, and demonstrates the implemented application’s uses.