Existing research on multimodal relation extraction (MRE) faces two co-existing challenges,
internal-information over-utilization and external-information under-exploitation. To combat …

Business Knowledge Graphs (KGs) are important to many enterprises today, providing
factual knowledge and structured data that steer many products and make them more …

Fusing data from different sources to improve decision making in smart cities has received
increasing attention. Collected data through sensors usually exist in a multi-modal form …

Knowledge graphs (KGs) are widely used in the education domain to offer learners a
semantic representation of domain concepts from educational content and their relations …

We present a large-scale empirical investigation of the zero-shot learning phenomena in a
specific recognizing textual entailment (RTE) task category, ie, the automated mining of …

In response to the exponential growth of the volume of scientific publications, researchers
have proposed a multitude of information extraction methods for extracting entities and …

The purpose of this work is to describe the orkg-Leaderboard software designed to extract
leaderboards defined as task–dataset–metric tuples automatically from large collections of …

Abstract Domain-specific named entity recognition (NER) on Computer Science (CS)
scholarly articles is an information extraction task that is arguably more challenging for the …

Recently, security attacks occurring in edge computing environments have emerged as an
important research topic in the field of cybersecurity. Edge computing is a distributed …

Science journalism refers to the task of reporting technical findings of a scientific paper as a
less technical news article to the general public audience. We aim to design an automated …