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There are mainly three types of problems in Peer-to-Peer (P2P) networks such as free-riding nodes, group deception, and node bias. To solve this, the authors proposed an incentive mechanism for the P2P networks based on feature weighting and game theory. The mechanism first used the five comprehensive coefficients of node degree, node clustering coefficient, local clustering coefficient, all clustering coefficients, and correlation coefficients to form a feature clustering matrix through lineardoi:10.18280/isi.250112 fatcat:qcec3dsonnc2jpacsdzijwa5bu