Rank Based Document Clustering and Summarization Approach in the Distributed P2P Network
Quick and high quality document clustering techniques play a vital role in text mining applications by grouping large text documents into meaningful clusters and enhancing the clustering accuracy using dimensionality reduction or query expansion. Detecting meaningful clusters and summaries in distributed P2P network applies single document summarization techniques and peer relationships for detecting meaningful clusters and summaries. Traditional cluster based summarization methods usually suffer with the computation speed, compression, peer selection and sentence clustering in order to generate high quality summaries.
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