In this decade, the music industry had a paradigm shift to digital distribution through online music stores and music streaming services, like Spotify, Apple Music, Amazon Music and SoundCloud. However, with the massive increase of available songs in the platforms, users of those encountered the problem of choosing suitable songs for them. Therefore, music recommendation systems became much more important to guide listeners to explore new songs suitable for their taste.

Mobile Devices has become more powerful since the first smartphone released. In the beginning, they are just UI tool for fast connection and reachability. However, they are now capable to execute intensive computational tasks. This brings the question, whether the task is executed in a server or not, in mind. In this project, we worked on this problem to find concrete results. Our implementations can divide into two parts, server and devices. In a server, we build a server gives responses to requests from our application.

NeuroBoun is an approach for advanced search services. User is offered domain specific types and constraints to expand his search. S/he can compare results and trace the movements in that area.

This project is basically an automatized  classification of websites into one of the predefined categories according to their topics. Using information retrieval principles and machine learning algorithms. This task is already done by humans for firms but web is an always growing, dynamic environment which makes maintenance a very cumbersome, never ending duty and this project aims to automatize this work.