Using Bio-inspired intelligence for Web opinion Mining

George Stylios, Christos D. Katsis, Dimitris Christodoulakis
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
more » ... algorithm (83.66%). The proposed methodology could be easily integrated with a decision support system providing services in the fields of ecommerce or e-government in order to help merchants acquire customer satisfaction or public administrators capture common understanding.
doi:10.5120/15207-3610 fatcat:di3rpxkio5dsbiw5s5ukbni46a