International Journal of Engineering and Technology

The development of Web 2.0 concept increased the web storage by offering information sharing from anywhere in the world. But how to use this content effectively and efficiently is the challenging task which is the important research in the field of Sentiment Analysis and Opinion Mining. This paper focus on these online data to process the web content using a pipeline processing which is applied to online reviews about products and generating a polarity checking tool for the user to provide them decision support information. Most of the research focuses on classification of polarities instead of pre-processing of data. But our idea is fine tuned pipeline processing will help us give better categorization. Classification has been achieved with many techniques, mainly depends on Machine Learning. This study also focuses on ranking using different classification techniques.