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User Activity Recognition through Software Sensors
Published in Qurban A. Memon, Distributed Networks, 2017
Stephan Reiff-Marganiec, Kamran Taj Pathan, Yi Hong
Context modelling specifies the context-related entities and relationship and the constraints between each other. Taking an example of our scenario, a user’s activity could be derived from his profile, calendar, timetable and email services. A context model provides the structure and methods to process the context data, which can be saved for later use. Context is quite wide ranging and includes, for example, a user profile information, the user’s location or planned activities, but generally it is quite varied [14]. After acquiring the user’s context, data need to be stored (at least while it is valid and of use), it will be reasoned upon or mined to extract knowledge to provide information needed by the context-aware systems or its users. A number of context-aware computing applications need information to be exchanged between entities, which might be user or services, and the context model should also support that interoperability.
A quantitative diary study of perceptions of security in mobile payment transactions
Published in Behaviour & Information Technology, 2021
Based on the definition of use context, it is a vital aspect of user behavior during mobile interactions. Many researchers have also explored specific contextual factors when studying user behavior or when designing general mobile services. Belk (1974) initially defined five situational factors that influence consumer behaviors: physical surroundings, social surroundings, temporal perspective, task definition, and antecedent states. Tarasewich (2003) has proposed a context model comprising three dimensions: environment, participants, and activity. Wigelius and Väätäjä (2009) have suggested five contextual factors that influence mobile use: social, spatial, temporal, infrastructural, and task context. Finally, Korhonen, Arrasvuori, and Väänänen-Vainio-Mattila (2010) have proposed eight contextual factors, namely environment, personal, task, social, spatio-temporal, device, service, and access network, to analyze the mobile user experience. In terms of security, different dimensions of use context influence user behaviors. For instance, Wolf, Kuber, and Aviv (2018) have proposed that applying context-sensitive technology could enhance security. Mallat (2007) has studied the influence of context on mobile payment usage and found that users’ security and privacy concerns are associated with authentication and confidentiality. These studies have discussed the influence of use context from a technology-based perspective. Dourish et al. (2004) have proposed that users’ perceptions of security depend not only on the nature of the task but also on who they interact with. This illustrates the influence of context from the perspective of social relationships.
A service governance mechanism based on process mining for cloud-based applications
Published in Enterprise Information Systems, 2018
Hongming Cai, Lida Xu, Boyi Xu, Pengzhu Zhang, Jingzhi Guo, Yuran Zhang
SceneInfo is used to describe a semantic scene or application condition to generate a comprehensive strategy for service governance in a cloud platform. It is a process-centric context model that contains process, tasks, services, and other feature data, such as task constraints, resource relations and task relations. The main parts and related models in the SSM are listed as follows.