The ongoing rapid expansion of the Internet greatly increases the necessity of effective
recommender systems for filtering the abundant information. Extensive research for …

The amount of information available online is increasing exponentially. While this
information is a valuable resource, its sheer volume limits its value. Many research projects …

Abstract While Artificial Intelligence in Education (AIED) research has at its core the desire to
support student learning, experience from other AI domains suggest that such ethical …

信息超载是目前网络用户面临的一个严重问题, 个性化推荐系统是解决该问题的一个有力工具,
并受到了众多的关注和研究. 给出推荐系统的定义, 同时阐述了推荐系统的几项关键技术 …

The massive adoption of technology in learning processes comes with an equally large
capacity to track learners. Learning analytics aims at using the collected information to …

ABSTRACT The Internet of Things paradigm envisions the pervasive interconnection and
cooperation of smart things over the current and future Internet infrastructure. The Internet of …

Recommender systems are an important part of the information and e-commerce ecosystem.
They represent a powerful method for enabling users to filter through large information and …

One of the potent personalization technologies powering the adaptive web is collaborative
filtering. Collaborative filtering (CF) is the process of filtering or evaluating items through the …

In this paper we integrate insights from diverse islands of research on electronic privacy to
offer a holistic view of privacy engineering and a systematic structure for the discipline's …

Intelligent data handling techniques are beneficial for users; to store, process, analyze and
access the vast amount of information produced by electronic and automated devices. The …