Flight web searches analytics through big data

被引：0

作者：

Khalil, Amna ^{[1
]}

Awan, Mazhar Javed ^{[2
]}

Yasin, Awais ^{[3
]}

Singh, Vishwa Pratap ^{[4
]}

Shehzad, Hafiz Muhammad Faisal ^{[5
]}

机构：

[1] Univ Management & Technol, Dept Comp Sci, Lahore 54770, Pakistan

[2] Univ Management & Technol, Dept Software Engn, Lahore 54770, Pakistan

[3] Natl Univ Technol, Dept Comp Engn, Islamabad 44000, Pakistan

[4] Guru Gobind Singh Indraprastha Univ, Sch Informat Commun & Technol, Delhi 110078, India

[5] Univ Sargodha, Dept Comp Sci & Informat Technol, Sargodha 40100, Punjab, Pakistan

来源：

INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY | 2022年 / 68卷 / 03期

关键词：

flights databases; search query; world wide web search engines; content-based retrieval; PREDICTION; IDENTIFICATION;

D O I：

10.1504/IJCAT.2022.10049751

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：260 / 268

页数：10

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