Cross-Lingual Document Retrieval Module Based on Hybrid Peer to Peer Network

Hybrid peer-to-peer architectures use special nodes to provide directory services for regions of the network ("regional directory services"), they are a potentially powerful model for developing large-scale networks of complex digital libraries. This paper proposes a content-based document retrieval model to hybrid peer-to-peer networks. This model sifts through large numbers of source texts in Chinese or in English which may be of the user\´s interest. Each text in the text set of the user\´s interest is represented as a vector in the vector space of classifiable sememes. The text to be sifted is represented as a vector too. The relevance of the text to the user can be measured by using the cosine angle between the text and its k nearest neighbors in the vector space. Experiments have been done and their results shown that this scheme yields good results