Manoj Jadhav

The huge increase in the e-commerce shopping has made customer reviews very important in decision making process of customer. The number of reviews for a single product can be quite high, especially for a most popular product. Many of the times consumer is interested in the overall sentiment of a product, so for this purpose they must first read all the reviews to come to a conclusion. And since reading huge number of reviews is a tedious process and may produce hinders in decision making… Show more

The huge increase in the e-commerce shopping has made customer reviews very important in decision making process of customer. The number of reviews for a single product can be quite high, especially for a most popular product. Many of the times consumer is interested in the overall sentiment of a product, so for this purpose they must first read all the reviews to come to a conclusion. And since reading huge number of reviews is a tedious process and may produce hinders in decision making. Therefore an efficient way of displaying the overall sentiment of a product based on costumer reviews is required.
This is the new research field and yet has not meet complete satisfaction. As finding explicit features is not sufficient to map complete review of the product, therefore we are proposing a system to extract implicit features as well as explicit features. Implicit features are not directly stated in the sentence but they are implied. The implicit features along with explicit features will help in giving correct feedback of various customers’ reviews about given product.
The proposed system will determine the implicit as well as explicit features of a product from customer reviews and produced overall feature based summary of the product.

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In cloud computing, data owners host their data on cloud servers and users (data consumers) can access the data from cloud servers. Due to the data outsourcing, however, this new paradigm of data hosting service also introduces new security challenges, which requires an independent auditing service to check the data integrity in the cloud. Some existing remote integrity checking method scan only serve for static archive data and, thus, cannot be applied to the auditing service since the data in… Show more

In cloud computing, data owners host their data on cloud servers and users (data consumers) can access the data from cloud servers. Due to the data outsourcing, however, this new paradigm of data hosting service also introduces new security challenges, which requires an independent auditing service to check the data integrity in the cloud. Some existing remote integrity checking method scan only serve for static archive data and, thus, cannot be applied to the auditing service since the data in the cloud can be dynamically updated. Thus, an efficient and secure dynamic auditing protocol is desired to convince data owners that the data are correctly stored in the cloud. In this paper, we first design an auditing framework for cloud storage systems and propose an efficient and privacy-preserving auditing protocol. Then, we extend our auditing protocol to support the data dynamic operations, which is efficient and provably secure in the random oracle model. We further extend our auditing protocol to support batch auditing for both multiple owners and multiple clouds, without using any trusted organizer. The analysis and simulation results show that our proposed auditing protocols are secure and efficient, especially it reduce the computation cost of the auditor. Show less