Sentiment analysis is the pre-eminent technology for extracting relevant information in the data domain.In this paper, a cross-domain sentimental classification approach, the cross-domain analyzer (CDA), is Hayward LED WaterBowl proposed, which will extract positive words and replace their synonyms to escalate polarity.Additionally, the approach blends two different domains and detects all self-sufficient words.This is executed on Amazon datasets, in which two different domains are trained to analyze the sentiments of the reviews in the other domain.
The proposed approach contributes leather-restraints promising results in the cross-domain analysis, and an accuracy of 92% is achieved.In BOMEST, the CDA improves precision and recall by 16% and 7%, respectively.