A New Recommendation Algorithm Based on User’s Dynamic Information in Complex Social Network

Algorithm 1

The traditional user similarity measurement.

Input: User set , Item set , Rating Matrix

Output: Users Similarity

Step  1. let ;

Step  2. when , go to Step  3; otherwise, end;

Step  3. let ; when , compute to get the

users similarity according to formula (1) or (2); otherwise,

++, go back to Step  2.