Research Article
Topological Influence-Aware Recommendation on Social Networks
Algorithm 1
The proposed recommendation method RDISI with direct and indirect social influence.
Input: List of training triples (user id, item id, rating), list of tuples (user id, trustee id), the | dimensionality of user feature vector and item feature vector , the learning rate , the | parameters , , and . | Output: User-user trust matrix, user-item rating matrix, local influence vector , global | influence vector , user feature matrix , and item feature vector . | 1: Generating user-item rating matrix and user-user trust matrix | for each triple do | | end for | for each tuple do | | end for | 2: Calculating local influence and global influence | for do | calculate | calculate using Eq. (3) | calculate | calculate using Eq. (4) | end for | 3: Initialize and randomly | while not convergence do | calculate according to Eq. (8) | calculate according to Eq. (9) | update | update | end while |
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