Summary
In a vertical organizational structure, component of a particular level has predetermined line of control from the objects of the management layer above it, but in horizontal organizational structure, objects of a layer are free to select the objects above them. The smart grid has a horizontal organizational structure compared to the power grid with vertical organization structure. This change in organizational structure always enabled independent operation of the components and demanding efficiency and profitability from these components. The distribution system of smart grid with a number of retailers in the market is relying on real‐time pricing to minimize the burden on consumers and to maximize its profit. In real‐time pricing, consumers are segmented based on their usage pattern and charged accordingly. In this paper, we formulated this complicated optimization problem and succeeded in computing real‐time selling prices for the consumers. For accurate and secure clustering, a new method is used, which is also well suitable for a big data environment like the smart grid. Consideration of price elasticity of consumers along with load profile, in the real‐time selling price determination, is the novelty of our paper. The optimization problem of profit maximization for retailers is solved using real‐time metering data collected from consumers in a smart grid pilot project in India. The results clearly show that real‐time prices for each class of consumers are according to their load profile.
E-commerce is evolving at such a rapid pace that new doors have been opened for users to have many opportunities to express their opinions about the product. The purpose of this project "Context Based Syntactic Opinion Mining" is to provide an effective way to view the opinions of the customers expressed in the form of customer reviews. This paper focus on aspect level opinion mining and proposes a new syntactic based approach using Natural Language Tool Kit (NLTK) and SentiWordNet. The objective of this paper is to summarize reviews of the product based on features or Aspects and classify as positive or negative opinion about a feature by assigning a score. This paper, mainly concentrates on reviews expressed about Mobile devices to extract the aspects but also applicable to other products. By analyzing the opinions of users about the features of a product, visual summary of the product can be made by plotting a graph based on score. It can also be extended to compare two mobile phone features and give an opportunity for the user to select the best among two products. This enables a user to have better understanding of the product which otherwise involves reading through long textual reviews to form a mental picture of the strengths and weaknesses of the product. This will be very useful for the customers to know about the features of product before making a buying decision. This project not only helps individuals in buying a product but also helps the organization to know how customers' perceive their product.
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