Skyline Query Optimization for Preferable Product Selection and Recommendation System

Abstract

Many social marketing systems use decision-making strategies for implementing product dominance analysis. The objective of the proposed work is to classify on-time issues in observing highly preferable market products, which is newer in online market places. Existing researches are interested to be useful for customers to identify the best possible products groups from the vast product details. To deal with this main objective, different types of product instances are reviewed. In this case, the price of popular products and the product groups are evaluated. This proposed system analyses the need for online market growth using novel skyline query analysis. The proposed system monitor user-based ratings affect the sales of various products. After finding the desirable products, the market prices are predicted. Once products are predicted, the new packages are assigned with optimal prices and added to the package database. Moreover, the proposed Skyline Query Optimization and Security Management System (SQOSMS) approach is focused on authorized user ratings and ensures they are more secured. The review system validates each and every user identities with the user activities involved with in review system. This is considered as major objective of this proposed system. The implementation section shows that the proposed system provides 10–15% of reduced movie lists than other systems. This illustrates the proposed SQOSMS’s controlled performance over the selection of preferable products.

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Correspondence to S. Rakesh Kumar.

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Soundararajan, R., Kumar, S.R., Gayathri, N. et al. Skyline Query Optimization for Preferable Product Selection and Recommendation System. Wireless Pers Commun (2020). https://doi.org/10.1007/s11277-020-07592-9

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Keywords

  • Social network
  • Product analysis
  • Online products
  • User security
  • Prices
  • Skyline and ratings