International Journal of Engineering and Technology

The use of social media sites as part of a company’s marketing strategy has increased significantly in the past couple years. Regardless its popularity, there is still very limited information to answer. Some of the key issues are concerning the effectiveness of social media marketing, and its target market. The emerging growth of online social networks has opened new doors for various business applications such as promoting a new product across its customers. However, the techniques being used in the online product purchasing system is not more flexible for the customer to get knowledge and information before purchasing the product, even user could take support of any other customer for the particular product who already purchased or used. To overcome on existing problems, we have proposed an enhanced approach with MD5, and Apriori Algorithm with Web clustering and Divide and conquer techniques. These proposed concepts are based on the user profile and consider the several users suggestion within their opinion for the perfect recommendation of the product. The user has to get the suggestion based on their profile and interest by completing the authorization process from the server or admin side. The Apriori algorithm is providing the product information or extract the product based on the user’s profile and their interest by continuing the security authentication from the admin side by using MD5 (Message Digest 5) algorithm. The Web cluster and Divide and Conquer technique is providing the better communication process for every particular user to get the complete information based on the different user’s review and poll. By proposing this enhancement the user getting a better suggestion for purchasing the product and the admin is adding the additional link of relevant product within the main product. The transaction process is getting support by the OTP security process, which is being performed within the Message Digest 5 (MD5) Algorithm.