{"title":"QoE影响因素(IFs)分类调查侧重于用户行为/粘性指标","authors":"Fatima Laiche, Asma BEN LETAIFA, T. Aguili","doi":"10.1109/WETICE49692.2020.00036","DOIUrl":null,"url":null,"abstract":"Over the last few years, the evolution of multimedia streaming services has resulted in growth and significant explorations of Quality of Experience (QoE) since the concept of QoE is gaining an enormous research effort, but it is still complex to estimate. This estimation can be influenced by a wide range of quality affecting factors. In this work, we provide standard definitions, we review and survey existing models to classify QoE Influence Factors (IFs). Moreover, we present a classification of the QoE IFs into four groups: system factors, context factors, human factors, and social-behavioral factors. Finally, regarding the QoE IFs, we highlight some relevant studies. We believe that our overview and findings can provide an understanding of the related quality affecting factors and QoE assessment approaches over video communications.","PeriodicalId":114214,"journal":{"name":"2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"QoE Influence Factors (IFs) classification Survey focusing on User Behavior/Engagement metrics\",\"authors\":\"Fatima Laiche, Asma BEN LETAIFA, T. Aguili\",\"doi\":\"10.1109/WETICE49692.2020.00036\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over the last few years, the evolution of multimedia streaming services has resulted in growth and significant explorations of Quality of Experience (QoE) since the concept of QoE is gaining an enormous research effort, but it is still complex to estimate. This estimation can be influenced by a wide range of quality affecting factors. In this work, we provide standard definitions, we review and survey existing models to classify QoE Influence Factors (IFs). Moreover, we present a classification of the QoE IFs into four groups: system factors, context factors, human factors, and social-behavioral factors. Finally, regarding the QoE IFs, we highlight some relevant studies. We believe that our overview and findings can provide an understanding of the related quality affecting factors and QoE assessment approaches over video communications.\",\"PeriodicalId\":114214,\"journal\":{\"name\":\"2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WETICE49692.2020.00036\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 29th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WETICE49692.2020.00036","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
QoE Influence Factors (IFs) classification Survey focusing on User Behavior/Engagement metrics
Over the last few years, the evolution of multimedia streaming services has resulted in growth and significant explorations of Quality of Experience (QoE) since the concept of QoE is gaining an enormous research effort, but it is still complex to estimate. This estimation can be influenced by a wide range of quality affecting factors. In this work, we provide standard definitions, we review and survey existing models to classify QoE Influence Factors (IFs). Moreover, we present a classification of the QoE IFs into four groups: system factors, context factors, human factors, and social-behavioral factors. Finally, regarding the QoE IFs, we highlight some relevant studies. We believe that our overview and findings can provide an understanding of the related quality affecting factors and QoE assessment approaches over video communications.