We present a method for querying knowledge graphs through natural language, emphasizing its application to the Greek language. It integrates NLP techniques with the capabilities of graph databases to enable seamless interaction with knowledge graphs ...

We present FlexRML, a flexible and memory efficient software resource for interpreting and executing RML mappings. As a knowledge graph materializer, FlexRML can operate on a wide range of systems, from cloud-based environments to edge devices, as ...

The increasing outsourcing by financial intermediaries intensifies the interconnection of the financial system with third-party providers. Concentration risks can materialize and threaten financial stability if these third-party providers are ...

Encyclopedic knowledge graphs, such as Wikidata, host an extensive repository of millions of knowledge statements. However, domain-specific knowledge from fields such as history, physics, or medicine is significantly underrepresented in those graphs. ...

Knowledge graphs have recently seen a wide range of applications in various domains. In many such applications data stored in relational databases constitutes an important source for the construction of knowledge graphs. R2RML is a mapping ...

With the emergence of AI technology, the application of artificial intelligence in education has been a popular topic in educational technology. Knowledge maps, the latest form of knowledge engineering in the field of AI, have significant research value ...

It is essential for large-scale knowledge graph construction to extract relation triplets composed of entity pairs and relations from unstructured texts. Although recent researches have made considerable progress in joint extraction of entities ...

Documents contain textual information, which is of the utmost importance for all the organizations. Document management systems have been used to store vast amounts of unstructured textual data described with minimal metadata, a method that has ...

This document summarizes the workshops and tutorials of the Extended Semantic Web Conference 2023. This edition accepted 10 workshops on different topics revolving around knowledge graphs, such as natural language processing, biomedical data, etc. ...

With the widespread growth of data on the Web, the need for efficient methods to get and arrange valuable information from these big noisy data is increased. The knowledge graph (KG) is a way to represent and organize the data in a ...

Knowledge Graphs (KGs) have gained considerable attention recently from both academia and industry. In fact, incorporating graph technology and the copious of various graph datasets have led the research community to build sophisticated graph ...

The number of scholarly publications grows steadily every year and it becomes harder to find, assess and compare scholarly knowledge effectively. Scholarly knowledge graphs have the potential to address these challenges. However, creating such graphs ...

Online social networks such as Facebook and LinkedIn have been an integrated part of everyday life. To improve the user experience and power the products around the social network, Knowledge Graphs (KG) are used as a standard way to extract and organize ...