Research Article
A Novel Travel Group Recommendation Model Based on User Trust and Social Influence
Algorithm 1
Group recommendation algorithm based on social influence and user trust recommendation.
| | Input: tourism user evaluation dataset , tourism user dataset U, scenic spot dataset , and parameters | | | Output: Top-K prediction rating of the group for the tourist attraction | | (1) | divide Groups | | (2) | for eachin | | (3) | calculate and | | (4) | end for | | (5) | for eachin | | (6) | for eachin | | (7) | calculate | | (8) | end for | | (9) | end for | | (10) | forto | | (11) | for each in Group | | (12) | | | (13) | | | (14) | | | (15) | end for | | (16) | Update recommendation scenic spot list | | (17) | end for | | (18) | return Top scenic spot |
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