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- W1982040456 abstract "The significant growing amount of shared files in distributed and serverless P2P networks has impacted heavily on content management and retrieval field. In this paper, we propose an associative memory network with intention to provide efficient pattern recognition within P2P networks. An efficient pattern recognition algorithm which works within distributed and dynamic nature of P2P network would be beneficial for better content handling and distribution. Our approach, which is called multi-wheel Graph Neuron (mWGN), is a variant of Graph Neuron (GN)-based algorithm built on top of Chord overlay network. GN algorithm is an associative memory designed for wireless sensor environment. mWGN is a restructured design from Hierarchical Graph Neuron (HGN), preserving its single cycle learning, lightweight and accuracy feature while requiring fewer number of nodes. Result from the experiment shows the proposed approach is highly accurate and the fault tolerance of Chord protocol provides stability for the proposed approach." @default.
- W1982040456 created "2016-06-24" @default.
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- W1982040456 date "2009-12-14" @default.
- W1982040456 modified "2023-10-16" @default.
- W1982040456 title "Multi-wheel graph neuron" @default.
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- W1982040456 doi "https://doi.org/10.1145/1806338.1806371" @default.
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