Abstract Multi-Source Information Fusion (MSIF), as a comprehensive interdisciplinary field
based on modern information technology, has gained significant research value and …

Relational machine learning studies methods for the statistical analysis of relational, or
graph-structured, data. In this paper, we provide a review of how such statistical models can …

The rapid increase of interest in, and use of, artificial intelligence (AI) in computer
applications has raised a parallel concern about its ability (or lack thereof) to provide …

The Industrial Internet-of-Things (IIoT) promises significant improvements for the
manufacturing industry by facilitating the integration of manufacturing systems by Digital …

Similar to humans, RL agents use interactive learning to successfully obtain satisfactory
decision strategies. However, in many cases, it is desirable to learn directly from …

An increasing number of information management and information exchange applications in
construction industry is relying on semantic web technologies or tools from the Linked Open …

The matrix-completion problem has attracted a lot of attention, largely as a result of the
celebrated Netflix competition. Two popular approaches for solving the problem are nuclear …

The representation of a knowledge graph (KG) in a latent space recently has attracted more
and more attention. To this end, some proposed models (eg, TransE) embed entities and …

An intelligent agent interacting with the real world will encounter individual people, courses,
test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of …

This paper describes a new paradigm of machine learning, in which Intelligent Teacher is
involved. During training stage, Intelligent Teacher provides Student with information that …