NU:BRIEF – A Privacy-aware Newsletter Personalization Engine for Publishers

09/08/2021
by   Ernesto Diaz-Aviles, et al.
0

Newsletters have (re-) emerged as a powerful tool for publishers to engage with their readers directly and more effectively. Despite the diversity in their audiences, publishers' newsletters remain largely a one-size-fits-all offering, which is suboptimal. In this paper, we present NU:BRIEF, a web application for publishers that enables them to personalize their newsletters without harvesting personal data. Personalized newsletters build a habit and become a great conversion tool for publishers, providing an alternative readers-generated revenue model to a declining ad/clickbait-centered business model.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 2

08/11/2015

Can JSP Code be Generated Using XML Tags?

Over the years, a variety of web services have started using server-side...
08/14/2020

Towards Querying in Decentralized Environments with Privacy-Preserving Aggregation

The Web is a ubiquitous economic, educational, and collaborative space. ...
07/05/2019

A Conceptual Marketplace Model for IoT Generated Personal Data

We propose a decentralized conceptual marketplace model for IoT generate...
06/13/2019

Trading Location Data with Bounded Personalized Privacy Loss

As personal data have been the new oil of the digital era, there is a gr...
05/26/2020

DimensionRank: Personal Neural Representations for Personalized General Search

Web Search and Social Media have always been two of the most important a...
07/30/2020

The Program with a Personality: Analysis of Elk Cloner, the First Personal Computer Virus

Although self-replicating programs and viruses have existed since the 19...
05/27/2019

Specific polysemy of the brief sapiential units

In this paper we explain how we deal with the problems related to the co...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.