Using tag similarity in SVD-based recommendation systems

Data analysis has become a very important area for both companies and researchers as a consequence of the technological developments in recent years. Companies are trying to increase their profit by analyzing the existing data about their customers and making decisions for the future according to the results of these analyses. Parallel to the need of companies, researchers are investigating different methodologies to analyze data more accurately with high performance. In this paper, we adopted free-formatted text-based tags into traditional 2-Dimensional SVD approach. We analysed the effect of different tag similarity techniques to the 3-Dimensional SVD recommendation performance. Our experiments illustrated that, tags increase the performance to some extent. The more similar tags means, the more accurate predictions.