Title: Flight web searches analytics through big data

Authors: Amna Khalil; Mazhar Javed Awan; Awais Yasin; Vishwa Pratap Singh; Hafiz Muhammad Faisal Shehzad

Addresses: Department of Computer Science, University of Management and Technology, Lahore 54770, Pakistan ' Department of Software Engineering, University of Management and Technology, Lahore 54770, Pakistan ' Department of Computer Engineering, National University of Technology, Islamabad 44000, Pakistan ' School of Information, Communication & Technology, Guru Gobind Singh Indraprastha University, Delhi 110078, India ' Department of Computer Science and Information Technology, University of Sargodha, Sargodha 40100, Punjab, Pakistan

Abstract: The flight search is considered one of the biggest searches on the World Wide Web. This study aims to establish an effective prediction model from a huge data set. This article offers a linear regression model to forecast flight searches using the big data framework SparkML library and statistics. Experiments on realistic data sets of domestic airports reveal that the suggested model's accuracy is close to 90% using the big data framework. Our research is provided an efficient flight web search engine, which can manage through big data.

Keywords: flights databases; search query; world wide web search engines; content-based retrieval.

DOI: 10.1504/IJCAT.2022.10049751

International Journal of Computer Applications in Technology, 2022 Vol.68 No.3, pp.260 - 268

Received: 10 Apr 2021
Accepted: 01 Jun 2021

Published online: 18 Aug 2022 *

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