A Bio-inspired Clustering Approach for Dynamic Document Distributed Analysis
نویسندگان
چکیده
Document clustering is a fundamental operation used in unsupervised document organization, automatic topic extraction and information retrieval. But most clustering technologies are limited in their application on the static document collection. Intelligence analysts are currently overwhelmed with tremendous amount of text information streams generated everyday. There is a lack of comprehensive tool that can real-time analyze the dynamic changed information streams. In this paper, we propose a bio-inspired clustering model, the Multiple Species Flocking clustering model (MSFC), and present a distributed multi-agent MSFC approach for clustering dynamic updated text information streams. The decentralized architectures and communication schemes of the MSFC multi-agent distributed implementation for load balance and status information synchronization are also discussed in this article.
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