Evaluation of sentiment analysis over bilingual cross domain platform using machine learning approaches

Abstract

Cross-Domain adaptation needs special data to get a shared characteristic with various domain. Notwithstanding, such valuable data may not generally be accessible in genuine cases. In this paper, another issue setting called Cross-Domain Sentiment Analysis in bilingual platform is addressed. It is an extraordinary instance of cross-space nostalgic examination in which diverse areas have some regular commonalities, yet in addition have their very own space explicit highlights. We influence upon normal highlights rather than beneficial data to accomplish viable adjustment. We propose a methodology, which can interface up various spaces utilizing normal highlights and at the same time decrease area divergences.