{"title":"等待还是购买:机票购买时机的推荐服务","authors":"Jian Cao, Yuchang Xu","doi":"10.1109/ICWS53863.2021.00031","DOIUrl":null,"url":null,"abstract":"In recent years, several optimal airline ticket purchasing strategies have been proposed and most of them are based on predicted price information. However, risks of ticket sold out and price uncertainties have not been modeled or considered by these strategies, which limits their effectiveness. Therefore, we design a recommendation service that is based on a new optimal airline ticket purchasing strategy PACES (Path Cost Expectation-based Strategy), which models and considers the risks and uncertainties of ticket purchasing explicitly. Extensive experiments are conducted on a real-world dataset and the results show that this strategy significantly outperforms the state-of-the-art techniques.","PeriodicalId":213320,"journal":{"name":"2021 IEEE International Conference on Web Services (ICWS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"To Wait or To Buy: A Recommendation Service for Airline Ticket Purchase Timing\",\"authors\":\"Jian Cao, Yuchang Xu\",\"doi\":\"10.1109/ICWS53863.2021.00031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, several optimal airline ticket purchasing strategies have been proposed and most of them are based on predicted price information. However, risks of ticket sold out and price uncertainties have not been modeled or considered by these strategies, which limits their effectiveness. Therefore, we design a recommendation service that is based on a new optimal airline ticket purchasing strategy PACES (Path Cost Expectation-based Strategy), which models and considers the risks and uncertainties of ticket purchasing explicitly. Extensive experiments are conducted on a real-world dataset and the results show that this strategy significantly outperforms the state-of-the-art techniques.\",\"PeriodicalId\":213320,\"journal\":{\"name\":\"2021 IEEE International Conference on Web Services (ICWS)\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE International Conference on Web Services (ICWS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWS53863.2021.00031\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Web Services (ICWS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWS53863.2021.00031","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
近年来,提出了几种最优机票购买策略,大多数都是基于预测价格信息的。然而,这些策略没有考虑门票售罄的风险和价格的不确定性,这限制了它们的有效性。因此,我们设计了一个基于新的最优机票购买策略pace (Path Cost expectation based strategy)的推荐服务,该策略明确地建模并考虑了机票购买的风险和不确定性。在真实世界的数据集上进行了广泛的实验,结果表明该策略明显优于最先进的技术。
To Wait or To Buy: A Recommendation Service for Airline Ticket Purchase Timing
In recent years, several optimal airline ticket purchasing strategies have been proposed and most of them are based on predicted price information. However, risks of ticket sold out and price uncertainties have not been modeled or considered by these strategies, which limits their effectiveness. Therefore, we design a recommendation service that is based on a new optimal airline ticket purchasing strategy PACES (Path Cost Expectation-based Strategy), which models and considers the risks and uncertainties of ticket purchasing explicitly. Extensive experiments are conducted on a real-world dataset and the results show that this strategy significantly outperforms the state-of-the-art techniques.