Comparison of Novel Semi supervised Text classification using BPNN by Active search with KNN Algorithm

With the availability of huge amount of text in internet, news, institutes, organization etc need of automatic text classification also increases, The proposed work comprised to deal with the major challenge of getting labeled data for training in classifier, since the availability of labeled data is expensive, time consuming, it also requires the involvement of annotator . A novel semi supervised test classification algorithm based on Back Propagation Neural Network is proposed which makes use of web assisted unlabeled data by Active search, this algorithm is compared with standard KNN algorithm on test data and standard data Mini Newsgroup. Experimental results state that the proposed algorithm outperforms KNN with Micro averaged F1measure.