Convex Optimization Algorithm for Product Recommendation Using Microblogging Information

The ecommerce and the social media is connected together where the products advertisements can be given by the ecommerce website which can be viewed by the social media users that is facebook users can  view the reviews given by the facebook friends or friends of friends of the users. The user may get an idea about the product features and also can be able to decide whether to buy the product or not. And also the user can give the review when the user knows about the product. In facebook database, all the reviews of the users or friends or friends of friends are stored. Among all the reviews, the overall count of the users who have given the positive comments and the negative comments are displayed .From this, the users can easily decide whether the product is useful or not. In the proposed system, convolutional neural network is used for more advanced learning

Hybrid Semi-Elastic Cluster for Resource Contraption in a Cloud

In the hybrid semi-elastic cluster both public and private customer like different organization such as Amazon, IBM, Infosys, etc., depends on data center to provide them resources. But suppose, a customer is not able to consume their resource is the given period, then there is a loss of remaining resources. So, we bring in a concept of returning remaining resources and providing them back whenever they are in use of it. Thus, as result resources are not been wasted and even validity of resources is increased. We introduce a concept of semi elastic cluster in which storage of resources can be increased at any point of time even if it full of traffic. Semi-elastic cluster performs various operations on it i.e., storing of data and all the resource with details of customers. A user return the resources to semi-elastic cluster and then further to data centers. And when user is again in use of it, it gets it back by requesting to semi-elastic cluster and further proceeds. Thus, in my project full resource will get utilized based on user’s demand with increase in validity