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/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Context reasoning is an important issue for a context-aware system. Generally, context reasoning is adopted to deduce new context based on the available contexts. The rule-based reasoning is one of the most well-known methods for context reasoning. However, it is difficult for the rule-based algorithm to reason personalized context, because it requires a large number of rules to apply the user's preferences. To address this weakness, in this paper we suggest the Profile-Applied Reasoning Engine (PARE). PARE is an enhanced rule-based reasoning method which uses profiles while reasoning contexts. By using profiles, PARE can become aware of the context that is preferred by a specific individual. To validate the effectiveness of the proposed reasoning engine, we compared the reasoning result of PARE with traditional rule-based reasoning in smart home domain. PARE shows better outcome for reasoning the personalized contexts than the traditional rule-based reasoning. In addition, by using profiles, a significant number of rules have been omitted and consequently the running time is also decreased. Moreover, PARE occupies less memory space which is restricted with number of variables of a rule. Therefore, PARE optimizes both runtime and memory space, which is valuable when making embedded context-aware system.

PARE: Profile-Applied Reasoning Engine for Context-Aware System