航空机票价格和需求的自动检测:综述

J. Abdella, Nazar Zaki, K. Shuaib
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引用次数: 8

摘要

预测机票价格和/或需求是非常具有挑战性的,因为它取决于各种内部和外部因素,这些因素可能在短时间内动态变化。研究人员提出了不同类型的机票价格/需求预测模型,目的是帮助客户预测机票价格或帮助航空公司预测需求。在本文中,我们介绍了客户端和航空公司端预测模型的回顾。我们的回顾分析表明,双方的模型都依赖于有限的特征集,如历史票价数据、购票日期和出发日期。外部因素的组合,如社交媒体数据和搜索引擎查询与先进的机器学习技术相结合,没有被考虑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Detection of Airline Ticket Price and Demand: A review
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.
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