Abstract
This paper tries to analyze Uber data set, and would implement business intelligence using Hadoop framework. This means by reducing the overhead and focusing on the routing optimization paths for a popular destination. However, there is dependably absence of straightforward and realistic techniques for choosing prominent destination. The paper tries to solve this problem by defining a threshold mechanism in order search the popular places. By, finding the days on which each place has more trips and more number of active vehicles by performing analysis on the Uber dataset in Hadoop using MapReduce in Java. Based on the data, find the top 20 destinations people travel the most, top 20 cities that generate high revenues for travel, based on booked trip count.
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Singhal, P., Vadivu, G. (2020). Cab Service Communication in Transportation Classification Techniques. In: Balaji, S., Rocha, Á., Chung, YN. (eds) Intelligent Communication Technologies and Virtual Mobile Networks. ICICV 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 33. Springer, Cham. https://doi.org/10.1007/978-3-030-28364-3_36
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DOI: https://doi.org/10.1007/978-3-030-28364-3_36
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