Automatic Detection of Airline Ticket Price and Demand: A review

Juhar Ahmed Abdella, Nazar Zaki, Khaled Shuaib

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Prediction of airline ticket prices and or demand is very challenging as it depends on various internal and external factors that can dynamically vary within short period of time. Researchers have proposed different types of ticket price/demand prediction models with the aim of either assisting the customer forecast ticket prices or aid the airline to predict the demand. In this paper, we present a review of customer side and airlines side prediction models. Our review analysis shows that models on both sides rely on limited set of features such as historical ticket price data, ticket purchase date and departure date. A combination of external factors such as social media data and search engine query in conjunction with advanced machine learning techniques are not considered.

Original languageEnglish
Title of host publicationProceedings of the 2018 13th International Conference on Innovations in Information Technology, IIT 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages169-174
Number of pages6
ISBN (Electronic)9781538666739
DOIs
Publication statusPublished - Jul 2 2018
Event13th International Conference on Innovations in Information Technology, IIT 2018 - Al Ain, United Arab Emirates
Duration: Nov 18 2018Nov 19 2018

Publication series

NameProceedings of the 2018 13th International Conference on Innovations in Information Technology, IIT 2018

Conference

Conference13th International Conference on Innovations in Information Technology, IIT 2018
Country/TerritoryUnited Arab Emirates
CityAl Ain
Period11/18/1811/19/18

Keywords

  • Deep Learning
  • Demand Prediction
  • Price Discrimination
  • Social Media
  • Survey
  • Ticket Price Prediction

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems and Management
  • Information Systems

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