{"title":"从海量在线评论中挖掘航空公司服务特色","authors":"Boyan Yao, Hua Yuan, Yu Qian, Liangqiang Li","doi":"10.1109/ICSSSM.2015.7170270","DOIUrl":null,"url":null,"abstract":"In this work, we propose a research framework to exploring the useful information about airline service from massive online reviews, especially, the airline service features from the customer perspective. The experimental results indicate that the proposed methods can extract information about customers' opinion about the airline service features. The common concerns as well as special features for different airline company can also be extracted efficiently from the massive online review data.","PeriodicalId":211783,"journal":{"name":"2015 12th International Conference on Service Systems and Service Management (ICSSSM)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"On exploring airline service features from massive online review\",\"authors\":\"Boyan Yao, Hua Yuan, Yu Qian, Liangqiang Li\",\"doi\":\"10.1109/ICSSSM.2015.7170270\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we propose a research framework to exploring the useful information about airline service from massive online reviews, especially, the airline service features from the customer perspective. The experimental results indicate that the proposed methods can extract information about customers' opinion about the airline service features. The common concerns as well as special features for different airline company can also be extracted efficiently from the massive online review data.\",\"PeriodicalId\":211783,\"journal\":{\"name\":\"2015 12th International Conference on Service Systems and Service Management (ICSSSM)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 12th International Conference on Service Systems and Service Management (ICSSSM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSSM.2015.7170270\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 12th International Conference on Service Systems and Service Management (ICSSSM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSSM.2015.7170270","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On exploring airline service features from massive online review
In this work, we propose a research framework to exploring the useful information about airline service from massive online reviews, especially, the airline service features from the customer perspective. The experimental results indicate that the proposed methods can extract information about customers' opinion about the airline service features. The common concerns as well as special features for different airline company can also be extracted efficiently from the massive online review data.