My thesis topic is the development of a personalized event recommendation web application. First I made a research about the available event portals. I realized that most of the Hungarian event portals are centralized, so the users do not have the possibility to publish their events and they do not have much option to interact with the application. These portals do not offer personalized event recommendation. This approach flips on the international market. Those websites operate with events uploaded by their users and usually have a recommendation algorithm implemented.
During my literature research I learnt about recommendation systems and algorithms and I reviewed the advantages and disadvantages of the different approaches.
I designed and implemented a platform where users with the right access can upload events and view statistics about the users behavior. Users can browse the events and they can apply for any event. Using a mixed technique of collaborative filtering and content based methods my solution is able to recommend events to the users based on their previous behavior. It is also able to find similar events, hosters or users. I used the Facebook Graph API to implement the Facebook authentication method into my web application.