关键词: 向量模型, 坐标空间, 降维, 资源搜索, 对等网络

Abstract:

A distributed semantic resources search mechanism for high-dimensional resources is presented. Faced with the problem that the similarity search with high-dimensional resources couldnt be effectively achieved in traditional peer-to-peer (P2P) network, a high-dimensional resource vector model is mapped to the low dimensional space based on dimensionality reduction algorithm based on principal component analysis and then projected to distributed hash table in P2P network which is a simple and effective way to achieve distributed similarity search. Meanwhile, the curse of dimensionality owing to the high dimension of resources could be prevented in the search. The maintenance of the similarity information after processing of dimensionality reduction is analyzed. Simulation based on content addressable network is shown the effectiveness of low-dimensional index built by dimensionality reduction algorithm. The mechanism will achieve a high precision ratio in distributed similarity search for the clustered high-dimensional resources.

Key words: vector model, coordinate space, dimension reduction, resources search, peer-to-peer network