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An Empirical Study on Package Query Processing System using Parallel Processing Mechanisms

General set-based inquiries pose several challenges in query processing systems in terms of time and space complexity. Most E-commerce platforms attract clients by offering smart chatbots. These systems use package inquiries, coupled with Artificial Intelligence [AI] systems to propose items that are more appealing to buyers, and they also collect people’s characteristics and preferences to match the replies more accurately. This research study has surveyed different package query systems developed by other researchers and found that the usage of Big Data tools help to store and map huge amount of data and it also helps them to retrieve the data as early as possible. It also found that the implementation of genetic based soft computing algorithms to reduce time complexity and answer the user query. The implementation of machine learning algorithm enhances the pre-processing and feature engineering procedures involved in the proposed research work.