Descriptive Naming of Context Data Providers

Much context data comes from mobile, transient, and unreliable sources. Such resources are best specified by descriptive names identifying what data is needed rather than which source is to provide it. The design of descriptive names has important consequences, but until now little attention has been focused on this problem. We propose a descriptive naming system for providers of context data that provides more flexibility and power than previous naming systems by classifying data providers into “provider kinds” that are organized in an evolving hierarchy of subkinds and superkinds. New provider kinds can be inserted in the hierarchy not only as subkinds, but also as superkinds, of existing provider kinds. Our names can specifyarbitrary boolean combinations of arbitrary tests on data-source attributes, yielding expressive power not found in naming schemes based on attribute matching.

By: Norman H. Cohen; Paul Castro; Archan Misra

Published in: Lecture Notes in Artificial Intelligence, volume 3554, (no ), pages 112-25 in 2005

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