Algorithm and application of collaborative filtering based on group dynamics.

As to the issue of scarce matrix and low recommendation accuracy in traditional collaborative filtering algorithm, this paper came up with an collaborative filtering algorithm based on group dynamics of social psychology model. The algorithm adjusted the traditional prediction methods taking fully individual factors and environmental factors into consideration, then recommended to users. Experimental results show that this algorithm can not only achieve better recommendation accuracy and alleviat the data sparsity obviously, but also reduce error accumulation effectively. At last, the algorithm was successfully applied to recommend service of Xi'an attractions. [ABSTRACT FROM AUTHOR]