The digital deep integration of cyber space, physical space and social space facilitates the
formation of Cyber–Physical–Social Systems (CPSS). Knowledge empowers CPSS to be …

Abstract Knowledge graph (KG) embedding models map nodes and edges to fixed-length
vectors and obtain the similarity of nodes as the output of a scoring function to predict …

Abstract Knowledge graphs are typical large-scale multi-relational structures and useful for
many artificial intelligence tasks. However, knowledge graphs often have missing facts …

Embedding methods map entities and relations to low-dimensional vectors and then use a
scoring function to predict missing links for knowledge graph completion. Most of the existing …

While natural language systems continue improving, they are still imperfect. If a user has a
better understanding of how a system works, they may be able to better accomplish their …

RPA technologies allow the automation of repeated processes through indirect or direct
instruction from the end-user. While declarative authoring techniques provide a powerful tool …

Recently, knowledge graphs have been broadly studied using approaches such as
translation-based models and convolutional neural networks. Although such approaches …

Web applications and services are increasingly important in a distributed internet filled with
diverse cloud services and applications, each of which enable the completion of narrowly …

Reasoning over knowledge graph explores valuable information for amounts of tasks.
However, most methods adopt the coarse-grained and single representation of each entity …

Edge labelling represents one of the most challenging processes for knowledge graph
creation in unsupervised domains. Abstracting the relations between the entities, extracted …