Knowledge Discovery from Text on a Cloud Architecture and its Application to Bioinformatics

Francesco Maiorana and Giacomo Fazio


Knowledge discovery from text, parallel clustering, cloud computing


In this paper we present a Knowledge Discovery from Text (KDT) framework and its applications to bioinformatics into a cloud architecture. The text mining framework consists of three building blocks: document retrieval and indexing; classification; and relevant class feature identification and discovery of associations. The proposed architecture is deployed on a private cloud architecture using the Eucalyptus project. A case study is described and results are reported.

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