Novel framework for data transformation for yielding structured data in opinion mining

Abstract

An effective data transformation is an integral requirement in order to facilitate an effective knowledge discovery mechanism on bigger scale of data. The proposed system considers the complexity associated with diverse opinion-based textual data that is shared by the user. Our review on existing system shows a big trade-off on implementing any form of simple transformation technique to address data volume and unstructured form of data. Therefore, the solution offered in this manuscript deals with identification of an explicit categories of data and extract the opinion shared for facilitating better sentiment analysis in future. Compared with the most frequently adopted software framework, our mechanism was found with faster response time and hence show better applicability in online analytical application associated with opinion mining operation for bigger data set