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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we propose a method to prioritize email using a trust network among users for supporting email triage, and evaluate its effectiveness with extensive experiments. In recent years, the amount of email received by individuals has increased, and therefore the time required for email triage (i.e., the process of going through unhandled email messages and deciding what to do with them) has therefore been increasing. Golbeck et al. proposed TrustMail, a prototype email client that prioritizes email in user’s mailbox using a trust network (i.e., a social network representing trust relationships among users). In this paper, we extend the TrustMail concept to allow message-based email prioritization using inter-recipient trust, which is inferred trust score from the recipient to other recipients. We propose a method called EMIRT (Estimating Message Importance from inter-Recipient Trust) for enabling message-based prioritization. Through extensive experiments utilizing two email datasets, we quantitatively evaluate the effectiveness of EMIRT for email prioritization. Our experimental results show that EMIRT is effective for email prioritization. Specifically, our results show that EMIRT achieves significantly higher recall and precision than TrustMail in both email datasets and that EMIRT hardly gives low scores to urgently replied email (i.e., EMIRT achieves a very low false negative).

Estimating Message Importance Using Inferred Inter-recipient Trust for Supporting Email Triage