Flight web searches analytics through big data
by Amna Khalil; Mazhar Javed Awan; Awais Yasin; Vishwa Pratap Singh; Hafiz Muhammad Faisal Shehzad
International Journal of Computer Applications in Technology (IJCAT), Vol. 68, No. 3, 2022

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.

Online publication date: Thu, 18-Aug-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com