Provide a data mining algorithm for text classification based on text content emotions using neural network

One of the newest areas of research is in data mining and text mining is automatic discovery of knowledge from semi-structured text. an important application of data mining in the classification texts.neural networks have emerged as a powerful tool in the classification of the content of texts and a promising alternative to conventional methods of classification. in this study, by combining and improving the regulatory procedure parameters weighted binary artificial neural network model, we will provide an algorithm to classify content. This algorithm content of the texts of the Persian texts will be based on the polarity of emotion suitable performance and high accuracy. The proposed algorithm is implemented using the simulation software MATLAB and evaluated collected over 1200 comments in Farsi in the real environment. The results above show that the proposed algorithm is a neural network classification accuracy of 96% negative polarity and positive polarity sentences based on document content.

Abstract licence: CC BY-NC

4 more references, whose wording the paper’s licence keeps private.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.