A Systematic BPCLSTM Algorithm for Concept Drift Detection Incorporated Sentiment Mining

Concept drift is a problem where context behind the word changes in different times as different. This happens ahead of the minimum stability period. Many applications are there in which the problem of the concept drift needs to be addressed, including online shopping preferences and review of the consumer, spam detection, climate change predictions and social stream data. In E-Commerce applications the concept drift plays a vital role in deciding the review and sentiment analysis. This research focus on the concept drift which impacts the sentiment mining. This research will provide a novel algorithm based on the deep learning recurrent neural network variant.