The basic idea of developing a new type of social media platform that not only allows users to find information, but to have a lot of fun, too, while also offering other companies high-quality, relevant market research was thought up by Stefan Gradl (business IT specialist) and two other computer scientists. The plan was to develop a platform capable of running entirely on its own and of making its own intelligent decisions to collect sustainable and usable information on users, click behaviour, etc. The image comparisons are the core and centrepiece of the portal. The comparison and analysis of images (products) is something new to the Internet. We are able to create more precise user profiles than other similar platforms and take advantage of the user’s desire to play games to optimise the fun factor in the user experience by actively integrating the user into this process. After an entire year of programming and development, the BETA version of WhitePins went online on 15 June 2012. We went in entirely new directions and wrote a unique and revolutionary piece of software to allow us to reach our ambitious goals. The secret algorithms and the genetic program code are the entirely unique differentiating feature of our software. Genetic algorithms are used to solve complex optimisation tasks. These algorithms are based on methods and insight taken from biological genetics. They were modelled on the theory of evolution, in which organisms that are better able to adapt to their environmental surroundings survive through natural selection. This evolutionary programming is able to constantly improve and develop based on the decisions made in the image comparisons. The software is completely independent. It makes its own decisions based on experience and insight gained in the field of genetics and constantly advances its own development. The result: user profiles that quickly adapt to changes in user behaviour and that contain very precise information. This greatly increases the hit rate for targeted marketing measures. We use the genetic algorithm to collect and improve information and to improve the quality of the user accounts.
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