Jie Gao, Lixia Liu, Zhang Tao, Shenghao Jia, Chuntao Song, Lexi Xu, Yang Wu, Bei Li, Yunyun Wang, Xinjie Hou
{"title":"基于大数据分析的用户投诉问题定位与投诉预警策略研究","authors":"Jie Gao, Lixia Liu, Zhang Tao, Shenghao Jia, Chuntao Song, Lexi Xu, Yang Wu, Bei Li, Yunyun Wang, Xinjie Hou","doi":"10.1109/trustcom56396.2022.00214","DOIUrl":null,"url":null,"abstract":"With the rapid development of mobile network, the use of mobile phones has become popular. People use mobile phones every day to surf the Internet, shop, socialize, work, etc. In the process of using mobile web services, users may be dissatisfied with the service perception, such as voice connectivity, Internet access, Slow Internet access and other common problems. If the customer is not satisfied with the communication service, the customer can usually complain about the quality of the communication service, so the frequency of the customer complaint has become an important evaluation index for the management of the operator. The quantity and frequency of customers ‘complaints about telecommunication service are increasing gradually, which brings challenges to the service quality and efficiency of telecommunication operators. This paper presents a methodology for customer complaints. The analysis system is based on the data of Horizontal pull- through, combined with big data analysis model, focus on the user’s response to the Internet slow, Internet access, voice access issues such as real-time positioning analysis, to provide customers with the first time solutions.","PeriodicalId":276379,"journal":{"name":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Research on User Complaint Problem Location and Complaint Early Warning Stragegy Based on Big Data Analysis\",\"authors\":\"Jie Gao, Lixia Liu, Zhang Tao, Shenghao Jia, Chuntao Song, Lexi Xu, Yang Wu, Bei Li, Yunyun Wang, Xinjie Hou\",\"doi\":\"10.1109/trustcom56396.2022.00214\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of mobile network, the use of mobile phones has become popular. People use mobile phones every day to surf the Internet, shop, socialize, work, etc. In the process of using mobile web services, users may be dissatisfied with the service perception, such as voice connectivity, Internet access, Slow Internet access and other common problems. If the customer is not satisfied with the communication service, the customer can usually complain about the quality of the communication service, so the frequency of the customer complaint has become an important evaluation index for the management of the operator. The quantity and frequency of customers ‘complaints about telecommunication service are increasing gradually, which brings challenges to the service quality and efficiency of telecommunication operators. This paper presents a methodology for customer complaints. The analysis system is based on the data of Horizontal pull- through, combined with big data analysis model, focus on the user’s response to the Internet slow, Internet access, voice access issues such as real-time positioning analysis, to provide customers with the first time solutions.\",\"PeriodicalId\":276379,\"journal\":{\"name\":\"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/trustcom56396.2022.00214\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/trustcom56396.2022.00214","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on User Complaint Problem Location and Complaint Early Warning Stragegy Based on Big Data Analysis
With the rapid development of mobile network, the use of mobile phones has become popular. People use mobile phones every day to surf the Internet, shop, socialize, work, etc. In the process of using mobile web services, users may be dissatisfied with the service perception, such as voice connectivity, Internet access, Slow Internet access and other common problems. If the customer is not satisfied with the communication service, the customer can usually complain about the quality of the communication service, so the frequency of the customer complaint has become an important evaluation index for the management of the operator. The quantity and frequency of customers ‘complaints about telecommunication service are increasing gradually, which brings challenges to the service quality and efficiency of telecommunication operators. This paper presents a methodology for customer complaints. The analysis system is based on the data of Horizontal pull- through, combined with big data analysis model, focus on the user’s response to the Internet slow, Internet access, voice access issues such as real-time positioning analysis, to provide customers with the first time solutions.