A P2P Network Information Retrieval Algorithm Optimization Simulation Analysis
Chunyan Chen · Science Technology and Engineering · 2013
In order to solve the P2P network information retrieval efficiency low,cannot effectively solve the cross text search,node interest domain clustering and information reputation incentive P2P network retrieval mechanism are put forward.In this mechanism,first of all,the data information which holds on the node of network system cluster with interest domain based on similarity and interest degree threshold,then,interest tree structure to interest adjacent nodes through the node data information reputation incentive strategy,the semantic analysis and personalized auxiliary semantic choice for users to enter search keywords,,returned to the user which hold node information and query information vector closest to the data and information for reputation incentive evaluation and update.The simulation results show that the algorithm can avoid structured P2P network system for center node excessive dependence based on the interest of the dynamic tree structure,and at the same time,retrieval vector is based on user personalized auxiliary semantic formation,can effectively improve the inquires the ratio and the precision ratio.