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This paper presents a document recommendation system based on clustering peer-to-peer networks. It's an unstructured P2P system. In this system each agent-peer can learn user's interest, then it helps user share and recommend documents with the other users. Since each peer in our P2P networks is a node, in order to cluster them, we import the concept of Group. Each group is composed of peers. The types of documents, which belong to a same group, are uniform. This paper presents how these peers help users to share and to recommend documents, and how they cluster into groups. Our experiment results show the advantages of the document recommendation system. [ABSTRACT FROM AUTHOR]

A novel PSO algorithm called InformPSO is introduced in this paper. The premature convergence problem is a deficiency of PSOs. First, we analyze the causes of premature convergence for conventional PSO. Second, the principles of information diffusion and clonal selection are incorporated into the proposed PSO algorithm to achieve a better diversity and break away from local optima. Finally, when compared with several other PSO variants, it yields better performance on optimization of unimodal and multimodal benchmark functions. [ABSTRACT FROM AUTHOR]

This paper presents our recent research work on Peer to Peer distributed information sharing based on mobile agent. From various perspectives, our work focuses on how to improve information retrieval efficiency in a P2P distributed information sharing system. A new model based on mobile agent is proposed and the new migration algorithm of mobile agent based on ant colony algorithm (ACA) is presented to implement P2P information retrieval. In order to evaluate and validate the model, we built a simulated P2P prototype consisting of a network of peer nodes; mobile agent migrating in the network, making peer nodes communication with each other. The results show some advantages of the proposed approach for the P2P distributed information sharing based on mobile agent. [ABSTRACT FROM AUTHOR]

As the collaborative editing system becomes prevalent, further requirement on content based collaboration is presented by editors. This paper focuses on how to implement content based collaboration. In order to combine the advantage of nature language processing technology in content parsing, we present the shallow nature language parsing technology in collaborative editing system. This technology is based on the segmentation and the text classification. This paper also discusses the reason why the shallow nature language parsing technology is useful in content based collaboration and its further use in collaborative editing system. In addition, it has already been used in our collaborative multimedia editing system which is designed for Chinese teaching material editor. From the result of experiment, it shows that the system really reduces the time in editing collaboration. [ABSTRACT FROM AUTHOR]

This paper presents our recent research work on mobile-agent based information content sharing in peer to peer system. Our work focuses on how to share the text content and recommend information based on mobile agent. The prototype uses terminology derived from the ant colony metaphor, including nest - a peer entity, and ant- an autonomous agent. Two mobile agents are proposed toimplementthe content-based text retrieval and information recommendation effectively. These agents are then evaluated through implementations and analysis. The simulated results demonstrate the advantages of our approach in the P2P system, and its potential applications in complex electric commerce and distributed information sharing. [ABSTRACT FROM AUTHOR]

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 presents our recent research work on the new content-based text filtering and collaborative filtering based on hybrid P2P (Peer-to-Peer) networks. From various perspectives, our work focuses on how to share the text content and recommend information based on hybrid P2P networks. Several models are proposed toimplementthe content-based text retrieval and collaborative filtering effectively. These models are then evaluated and validated through implementations and analyses. The results show some advantages of the proposed approach for the content-based filtering algorithm based on lexical chain and collaborative filtering algorithm in hybrid P2P network and potential applications in complex digital libraries and distributed information sharing. [ABSTRACT FROM AUTHOR]