Data Analytics for Air Travel Data: A Survey and New Perspectives

航空旅行 计算机科学 大数据 分析 数据科学 航空运输 数据分析 航空 运筹学 运输工程 数据挖掘 工程类 航空航天工程
作者
Haiman Tian,Maria Presa-Reyes,Yudong Tao,Tianyi Wang,Samira Pouyanfar,Alonso Miguel,Steven Luis,Mei‐Ling Shyu,Shu‐Ching Chen,Sundaraja Sitharama Iyengar
出处
期刊:ACM Computing Surveys [Association for Computing Machinery]
卷期号:54 (8): 1-35 被引量:31
标识
DOI:10.1145/3469028
摘要

From the start, the airline industry has remarkably connected countries all over the world through rapid long-distance transportation, helping people overcome geographic barriers. Consequently, this has ushered in substantial economic growth, both nationally and internationally. The airline industry produces vast amounts of data, capturing a diverse set of information about their operations, including data related to passengers, freight, flights, and much more. Analyzing air travel data can advance the understanding of airline market dynamics, allowing companies to provide customized, efficient, and safe transportation services. Due to big data challenges in such a complex environment, the benefits of drawing insights from the air travel data in the airline industry have not yet been fully explored. This article aims to survey various components and corresponding proposed data analysis methodologies that have been identified as essential to the inner workings of the airline industry. We introduce existing data sources commonly used in the papers surveyed and summarize their availability. Finally, we discuss several potential research directions to better harness airline data in the future. We anticipate this study to be used as a comprehensive reference for both members of the airline industry and academic scholars with an interest in airline research.
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