Focused on the issue that existing group recommendation methods take less account of the implicit estimation of socialization relationships among group members and the use of group consensus to reduce the influence of preference conflicts， a Group Recommendation method based on implicit Trust and group Consensus （GR-TC） was proposed. The method was divided into a recommendation phase and a consensus phase. In the recommendation phase， implicit trust values were mined based on preference information and social relationships among members. The members’ individual preferences and weights， and the initial group preferences were estimated. In the consensus phase， inconsistent members were identified by consensus measurement and identification rules， a maximum harmony optimization consensus model was built， and the group recommendation list was obtained by adjusting and updating the group preferences. Experimental results show that social relationships among members affect group recommendation results， reasonable selection of implicit trust weights improves the harmony of inconsistent members. Compared with the traditional consensus feedback mechanism， the implicit trust-induced maximum harmony consensus feedback mechanism has less adjustment cost and less impact on inconsistent members.

To make use of the social relationship between experts and to consider the limited rationality of decision-making experts in group decision-making， a TODIM （TOmada de Decis?o Interativa Multicritério） group decision-making method under trust network was proposed. Firstly， according to the number of discussions of the experts， in each discussion， each expert would refer to his/her trustee’s decision matrix according to the degree of trust acceptance， and the decision matrices would be modified through information interaction and negotiation. Then， when the set number of expert discussions was met， the final group decision-making matrix was calculated. Finally， the TODIM group decision-making method under trust network and TODIM group decision-making method were applied to calculate the ranking results of different schemes. The ranking results were compared and analyzed， and the sensitivity analysis was performed on the number of expert discussions and trust acceptance. The case analysis results show that the TODIM group decision-making method under trust network can fully integrate trust network， ensure the multi-stage information interaction and feedback process in the decision-making process， and is superior to the general TODIM group decision-making method in comparison analysis and sensitivity analysis.