Nowadays, products are offered to buyers in different varieties and qualities on the Internet environment. Recommedation systems are needed to make the right choices and make effective decisions. The article offers a new method and algorithm based on data obtaned through different ways and by creating hybrid recommendation systems. Estimation method is given based on information about objects and users for proper development of the algorithm. The proposed method can identify the proximity between the users group and the objects the users are interested in.
Internet-advertising data, Hybrid recommendation systems Filtration, Collaboration filter, Proximity measure.
This study received no specific financial support.
The authors declare that they have no competing interests.