Abstract
Context-awareness has become a key issue in Human-Computer Interaction(HCI) to provide better user experience under multi-device and multi-modal environment. With this intuition, we have proposed a web service based framework, which associates interactions with services, and provided service selection mechanism using context knowledge to achieve smart interaction migration [1]. A fundamental problem of such a service-oriented framework for interaction migration is to design an effective while scalable algorithm for service selection. In this paper, we propose a service selection algorithm considering not only context information and user preferences but also inter-service relations such as relative location. Our algorithm detects interaction hot spots within user active scope and presents the best service combination based on evaluation of interaction effectiveness. We also conduct simulation and the results illustrate that our algorithm is effective and scalable for interaction service selection.
Highlights
Computer systems play a prime role in support of information delivery
Traditional HCI is restricted to one-one mode, that is one user only interacts with one device like personal computer through a few communication channels such as mouse and keyboard
The basic idea of our design is that when encountering interaction migration, users are usually inexpert in deciding the target platform because they do not hold the insight into device capability and compatibility
Summary
Computer systems play a prime role in support of information delivery. Generally, the effectiveness of information systems largely relies on two factors: information quality and presentation. Since a majority of commercial information systems support and provide services, the nature and progression of the service encounter should be a key concern of human computer interface designers [4] This service-oriented HCI concept transforms interaction migration problem to service selection problem and attempts to find solutions from web service selection techniques. With these concerns, we present in this paper a new context-aware HCI service selection process which keeps the flexibility of service-oriented concepts and replaces the original selection algorithm with a new scalable algorithm utilizing both user and inter-service contexts. This service-oriented concept generalizes interaction types and makes it possible to migrate interaction to multiple devices and modalities
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