Knowledge Graph Definition - From Twente University

Na palestra do Giancarlo no SBBD 2023 ele comentou que uma das primeiras definições sobre Knowledge Graphs veio da Universidade de Twente (onde ele está lecionando / pesquisando atualmente) 

Encontrei no Survey sobre Definições de KG o seguinte trecho:

In the 1980s, researchers from the University of Groningen
and the University of Twente in the Netherlands initially
introduced the term knowledge graph to formally describe
their knowledge-based system that integrates knowledge from
different sources for representing natural language [10, 15].
The authors proposed KGs with a limited set of relations and
focus on qualitative modeling including human interaction,
which clearly contrasts with the idea of KGs that has been
widely discussed in recent years.

Survey: Towards a Definition of Knowledge Graphs. Lisa Ehrlinger and Wolfram Wöß. Institute for Application Oriented Knowledge Processing. Johannes Kepler University Linz, Austria

[10] P. James. Knowledge Graphs. In Linguistic. Instruments in Knowledge Engineering, pages 97–117.
Elsevier Science Publishers B.V., 1992.

[15] S. Nurdiati and C. Hoede. 25 Years Development of Knowledge Graph Theory: The Results and the Challenge, September 2008.

[Em 2008 já eram 25 anos de desenvolvimento de KGs ... Hoje são 40 anos !!!]

Nesta publicação de 25 anos de pesquisa temos:

The basic idea of the theory is that in the mind representation of the world is present
that has a discrete mathematical nature, so can be modelled by a knowledge graph, that is called
mind graph. The vertices of this graph correspond to somethings, the genus of all concepts.
"Something" may be a perception unit, then is represented by a single token but, more generally,
will be a complex structure of tokens that are linked by links of certain types. 

 

No livro sobre KG do Aidan et al achei esta referência de 1987

Bakker (1987) [27] defines a knowledge graph with the purpose of cumulatively representing content gleaned from medical and sociological texts, with a focus on causal relationships. Work on knowledge graphs from the same group would continue over the years, with contributions by Stokman and de Vries (1988) [501] further introducing mereological (part of ) and instantiation (is a) relations to the knowledge graph, and thereafter by James [266] , Hoede [242] , Popping [419] , Zhang [576] , amongst others, in the decades that followed [ 389 ]. The notion of knowledge graph used in such works considered a fixed number of relations. Other authors pursued their own parallel notions of knowledge graphs towards the end of the 80’s

[27] René Ronald Bakker. 1987. Knowledge Graphs: Representation and Structuring of Scientific Knowledge. Ph.D. Dissertation. University of Twente.

No site da universidade existem várias publicações com a expressão "knowledge graph"

https://www.utwente.nl/en/?q=%22knowledge+graph%22 

Em uma publicação de 2022 temos

THE KNOWLEDGE GRAPH AS THE INTEROPERABILITY FOUNDATION FOR AN
AUGMENTED REALITY APPLICATION: THE CASE AT THE DUTCH LAND REGISTRY

The Knowledge Graph (KG), a data representation model in
which data is stored as a graph comprised of nodes and edges
mapped to ontologies to form a semantic network, was
introduced as a means of connecting and integrating data
from different sources. Indeed, a knowledge graph or
semantic network can be defined as representing ‘a network
of real-world entities – i.e. objects, events, situations or
concepts – and illustrates the relationship between them’ [2].

Quanto as definições, na pesquisa adotamos que KG são KB do tipo semantic networks (além das entidades, os relacionamentos também estão no foco da análise). Mas existem diferenças em relação a KB e Ontologias, em termos de escala, utilização de algoritmos de grafo e raciocínio neuro simbólico bem como engenharia Bottom-Up, com apoio de engenheiros e com métodos automáticos.

No survey, mencionado no início, quanto a diferenças, temos: 

Thus, the difference between a knowledge graph and an ontology could be interpreted either as a matter of quantity (e.g., a large ontology), or of extended requirements (e.g., a built-in reasoner that allows new knowledge to be derived).

The second interpretation leads to the assumption that a knowledge graph is a knowledge-based system that contains a knowledge base and a reasoning engine.

This definition aligns with the assumption that a knowledge graph is somehow superior and more complex than a knowledge base (e.g., an ontology) because it applies a reasoning engine to generate new knowledge and integrates one or more information sources.