{"title":"移动交互分析:迈向交互序列挖掘的新概念","authors":"Florian Lettner, C. Grossauer, Clemens Holzmann","doi":"10.1145/2628363.2628384","DOIUrl":null,"url":null,"abstract":"Identifying intentions of users when they launch an application on their smartphone, and understanding which tasks they actually execute, is a key problem in mobile usability analysis. First, knowing which tasks users actually execute is required for calculating common usability metrics such as task efficiency, error rates and effectiveness. Second, understanding how users perform these tasks is important for developers in order to validate designed interaction sequences for tasks (e.g. sequential steps required to successfully perform and complete a task). In this paper, we describe a novel approach for automatically extracting and grouping interaction sequences from users, assigning them to predefined tasks (e.g. writing an email) and visualising them in an intuitive way. Thus, we are able to find out if the designer's intention of how users should perform designed tasks, and how they actually execute them in the field, matches, and where it differs. This allows us to figure out if users find alternate ways of performing certain tasks, which contributes to the application design process. Moreover, if the users' perception of tasks differs from the designer's intention, we lay the foundation for recognising issues users may have while executing them.","PeriodicalId":74207,"journal":{"name":"MobileHCI : proceedings of the ... International Conference on Human Computer Interaction with Mobile Devices and Services. MobileHCI (Conference)","volume":"79 1","pages":"359-368"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Mobile interaction analysis: towards a novel concept for interaction sequence mining\",\"authors\":\"Florian Lettner, C. Grossauer, Clemens Holzmann\",\"doi\":\"10.1145/2628363.2628384\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Identifying intentions of users when they launch an application on their smartphone, and understanding which tasks they actually execute, is a key problem in mobile usability analysis. First, knowing which tasks users actually execute is required for calculating common usability metrics such as task efficiency, error rates and effectiveness. Second, understanding how users perform these tasks is important for developers in order to validate designed interaction sequences for tasks (e.g. sequential steps required to successfully perform and complete a task). In this paper, we describe a novel approach for automatically extracting and grouping interaction sequences from users, assigning them to predefined tasks (e.g. writing an email) and visualising them in an intuitive way. Thus, we are able to find out if the designer's intention of how users should perform designed tasks, and how they actually execute them in the field, matches, and where it differs. This allows us to figure out if users find alternate ways of performing certain tasks, which contributes to the application design process. Moreover, if the users' perception of tasks differs from the designer's intention, we lay the foundation for recognising issues users may have while executing them.\",\"PeriodicalId\":74207,\"journal\":{\"name\":\"MobileHCI : proceedings of the ... International Conference on Human Computer Interaction with Mobile Devices and Services. MobileHCI (Conference)\",\"volume\":\"79 1\",\"pages\":\"359-368\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MobileHCI : proceedings of the ... International Conference on Human Computer Interaction with Mobile Devices and Services. MobileHCI (Conference)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2628363.2628384\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MobileHCI : proceedings of the ... International Conference on Human Computer Interaction with Mobile Devices and Services. MobileHCI (Conference)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2628363.2628384","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mobile interaction analysis: towards a novel concept for interaction sequence mining
Identifying intentions of users when they launch an application on their smartphone, and understanding which tasks they actually execute, is a key problem in mobile usability analysis. First, knowing which tasks users actually execute is required for calculating common usability metrics such as task efficiency, error rates and effectiveness. Second, understanding how users perform these tasks is important for developers in order to validate designed interaction sequences for tasks (e.g. sequential steps required to successfully perform and complete a task). In this paper, we describe a novel approach for automatically extracting and grouping interaction sequences from users, assigning them to predefined tasks (e.g. writing an email) and visualising them in an intuitive way. Thus, we are able to find out if the designer's intention of how users should perform designed tasks, and how they actually execute them in the field, matches, and where it differs. This allows us to figure out if users find alternate ways of performing certain tasks, which contributes to the application design process. Moreover, if the users' perception of tasks differs from the designer's intention, we lay the foundation for recognising issues users may have while executing them.