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Using Bio-inspired intelligence for Web opinion Mining
2014
International Journal of Computer Applications
This work proposes a bio-inspired based methodology in order to extract and evaluate user's web texts / posts. To validate the methodology, a dataset is constructed using real data arising from Greek fora. The obtained results are compared with a commonly used machine learning technique (decision trees-C4.5 algorithm). The bio-inspired algorithm (namely the hybrid PSO/ACO2 algorithm) achieved average classification accuracy 90.59% in a 10 fold cross validation experiment, outperforming the C4.5
doi:10.5120/15207-3610
fatcat:di3rpxkio5dsbiw5s5ukbni46a