The reviews of customers in E-Commerce Systems are typically considered key resources, are reflecting the experiences, sentiments, and readiness of the customer to buy products. All such data may include perspectives of customers on matters of interest, feelings, and opinions. Various studies have demonstrated that individuals with comparable attitudes about the topics are more inclined to trust one another. This study explores searching for and adopting e-commerce services with sentimentsand recommendations that involve some customer trust.A trust-based model for the E-commerce application (TM-ECA) model is proposed in this article. From that perspective, an e-commerce system examines a strategy for examining sentimental similarities based on mining to examine consumers' similarities and confidence. Trust is divided into two classifications: direct trust and common trust that is a connection of trust among two people. The direct level of trust is acquired through feeling resemblance, and a pair of words for retrieving comparable characteristics isavailable.The transitivity characteristic determines the spread of trust. The smallest path is selected to express confidence and offer an enhanced smallest path method to identify the link between consumers' confidence in transmission using the suggested confidence model. To check the correctness and practicality of methods and the designs, a website for e-commerce evaluates the method. The testing results show that the sentimental evaluation of resemblance can be an effective way of finding confidence among e-commerce system customers.