16 research outputs found
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Preface of MEPDaW 2020: Managing the evolution and preservation of the data web
The MEPDaW workshop series targets one of the emerging
and fundamental problems of the Web, specifically the management and
preservation of evolving knowledge graphs. During the past six years,
the workshop series has been gathering a community of researchers and
practitioners around these challenges. To date, the series has successfully
published more than 30 articles allowing more than 50 individual authors
to present and share their ideas.
This 6th edition, virtually co-located with the International Semantic
Web Conference (ISWC 2020), gathered the community around nine research publications and one invited keynote presentation. The event took
place online on the 1st of November, 2020
Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs
Inductive link prediction -- where entities during training and inference
stages can be different -- has been shown to be promising for completing
continuously evolving knowledge graphs. Existing models of inductive reasoning
mainly focus on predicting missing links by learning logical rules. However,
many existing approaches do not take into account semantic correlations between
relations, which are commonly seen in real-world knowledge graphs. To address
this challenge, we propose a novel inductive reasoning approach, namely TACT,
which can effectively exploit Topology-Aware CorrelaTions between relations in
an entity-independent manner. TACT is inspired by the observation that the
semantic correlation between two relations is highly correlated to their
topological structure in knowledge graphs. Specifically, we categorize all
relation pairs into several topological patterns, and then propose a Relational
Correlation Network (RCN) to learn the importance of the different patterns for
inductive link prediction. Experiments demonstrate that TACT can effectively
model semantic correlations between relations, and significantly outperforms
existing state-of-the-art methods on benchmark datasets for the inductive link
prediction task.Comment: Accepted to AAAI 202
Preface of MEPDaW 2022: Managing the Evolution and Preservation of the Data Web
[no abstract available
ChImp:Visualizing Ontology Changes and their Impact in Protégé
Today, ontologies are an established part of many applications and research.
However, ontologies evolve over time, and ontology editors---engineers and domain experts---need to be aware of the consequences of changes while editing.
Ontology editors might not be fully aware of how they are influencing consistency, quality, or the structure of the ontology, possibly causing applications to fail.
To support editors and increase their sensitivity towards the consequences of their actions, we conducted a user survey to elicit preferences for representing changes, e.g., with ontology metrics such as number of classes and properties.
Based on the survey, we developed ChImp---a Protégé plug-in to display information about the impact of changes in real-time.
During editing of the ontology, ChImp lists the applied changes, checks and displays the consistency status, and reports measures describing the effect on the structure of the ontology.
Akin to software IDEs and integrated testing approaches, we hope that displaying such metrics will help to improve ontology evolution processes in the long run
Semantic Knowledge Graphs for the News: A Review
ICT platforms for news production, distribution, and consumption must exploit the ever-growing availability of digital data. These data originate from different sources and in different formats; they arrive at different velocities and in different volumes. Semantic knowledge graphs (KGs) is an established technique for integrating such heterogeneous information. It is therefore well-aligned with the needs of news producers and distributors, and it is likely to become increasingly important for the news industry. This article reviews the research on using semantic knowledge graphs for production, distribution, and consumption of news. The purpose is to present an overview of the field; to investigate what it means; and to suggest opportunities and needs for further research and development.publishedVersio