English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Context-awareness refers to systems that unobtrusively adapt to the environment of their users on the basis of context information, popularly known as context-aware systems. One inherent property of context information is that it possesses a certain quality, such as the certainty with which it has been determined and so on. Different aspects of this quality are represented by a set of indicators collectively known as Quality of Context (QoC). QoC also represents privacy sensitiveness of context information, i.e. context information of higher quality is considered more privacy sensitive. An important step towards making QoC indicators usable is to quantify them in tangible units. In this paper we provide motivation for using QoC indicators as meta-information for context management and use QoC as part of a user privacy enforcement framework. We propose five QoC indicators and present different alternatives available for expressing them quantitatively

Quality-of-Context and its use for Protecting Privacy in Context Aware Systems