A hybrid classifier approach for Web retrieved documents classification

The paper presents a hybrid technique for the classification of web returned hits into concept hierarchies. The technique involves a combination of manual and automatic classifiers. At first, all web returned documents are assigned to human defined categories using manual classifiers, and then automatic classifiers are used to generate a concept hierarchy for each of these categories. The results of the evaluation reveal the following: (a) for polysemous queries, our system is able to generate meaningful categories corresponding to (but not limited to), the different semantic facets of the queries; (b) as expected, for non-polysemous queries the system generates fewer categories; (c) the hierarchy precision of the concept hierarchies generated for polysemous queries is found to be significantly better when compared to the one obtained using a baseline system.