Kademlia protocol has been studied carefully in this paper. The Kademlia mechanism based on interest is proposed to support approximate search. The interest eigenvector is used to represent the peer's interest. Moreover the interest router table that stores the peers' interest information replaces the original one. Especially as a part of the interest router table, each K-bucket stores a certain number of the peers' information that have high interest similarity. The query can be executed in the appropriate k-bucket by calculating interest similarity and interest keyword. Through mining the latent interest, we found that two peers having high interest similarity are more possible to store the similar resource. Because the character restricts the query to a certain scope, the approximate search is realized and search efficiency is improved. The experiments show that the improved search mechanism obviously increases the recall, at the same time effectively reduces the number of visited peers.
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