Top-k Dominating Queries on Skyline Groups
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Product Description
Aim
The main aim of this paper is to study the problem of secure skyline
queries over encrypted data. The skyline query is particularly important for
multi-criteria decision making but also presents significant challenges due to
its complex computations.
Synopsis
The emerging computing paradigm, cloud computing attracts increasing attention from both research and industry communities. Outsourcing data and computation to cloud server provides a cost effective way to support large scale data storage and query processing. However, due to security and privacy concerns, sensitive data need to be protected from the cloud server as well as other unauthorized users. In this paper we focus on the problem of secure skyline queries on encrypted data, another type of similarity search important for multi-criteria decision making. The skyline or Pareto of a multi-dimensional dataset given a query point consists of the data points that are not dominated by other points. A data point dominates another if it is closer to the query point in at least one dimension and at least as close to the query point in every other dimension. The skyline query is particularly useful for selecting similar (or best) records when a single aggregated distance metric with all dimensions is hard to define.
Proposed System
In the proposed system, there is bit of
communication between the data owner and user about the price of the product.
If the user is not satisfied with the price given by the seller user can bargain
for the price and can reduce the price .Then the user got offer with the
related products by combo with others.
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