Re: Is scalability the key property of knowlege graph?

See:https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines#Top
And download the Definition of AI by the High-Level Expert Group.
Look at figure 1: A schematic depiction of AI. This figure can be generalized with category theory to reflect (1) the practice of empirical science, (2) decidability in theory of computation, (3) formal proof of Godel for incompleteness, (4) description of sentient beings (and possibly also intelligent) interacting with their environment, (5) Buddhist logic on falsehood of perception of external realities through our fallible senses, (6) modeling our formal interpretations of quantum reality and abstract mathematical spaces, (7) modeling information theory limitations of observed environment in terms of formal description and algorithms for decision-making.
So knowledge representation and how we create knowledge, either based on formal reasoning or experience (formal theory or massive amounts of data based deep learning) are two essential elements of any trustworthy, ethical and robust AI system.

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    On Thursday, June 13, 2019, 9:56:05 AM EDT, Franconi Enrico <franconi@inf.unibz.it> wrote:  
 
 You may find this summary about the current practice and research on KGs interesting:https://www.juansequeda.com/blog/2018/09/18/trip-report-on-knowledge-graph-dagstuhl-seminar/And, yes, I believe that a KG is basically an RDFs graph grounded to some sort of reality.In terms of KR practice, KGs are an amazing leap backwards to the good old semantic nets of the 70ies.This is not to say that they don't play a useful role within Google technologies or similar stuff.cheers --e.


Il giorno 13 giu 2019, alle ore 12:10, Chris Harding <chris@lacibus.net> ha scritto:
What is a knowledge graph? 

I looked it up in Wikipedia, and the definition seemed to be "What Google does". Reading a bit more widely, I came to the conclusion that it is a triple store to which someone attaches meaning. (Of course, this is most, if not all, triple stores.) What is interesting is the impressive amount of theory and practice, associated with the "knowledge graph" label, for using AI and other techniques to obtain transformations or measurements of the triple stores that add to the meaning that people attach to them.

I found these articles helpful:
http://ceur-ws.org/Vol-2322/dsi4-6.pdf
https://towardsdatascience.com/neural-network-embeddings-explained-4d028e6f0526
https://content.iospress.com/articles/data-science/ds007

xyzscy wrote:

Thank you for your response. I think the KG term is spread by GOOGLE, while I don’t how google implement it.  I used to think the semantic network  is the key technology of KG,but google has never statement that.

在 2019年6月13日，下午2:46，Paola Di Maio <paola.dimaio@gmail.com> 写道：
Thank you for asking this, 
I  ll leave the experts to reply to scalability and other questions
In general, much depends on the language one uses, which in turndepends on the domain (which planet you come from)
When I first studied knowledge engineering, the expression knowledge graphwas not in use at all. I was doing an MSc and studied the body of knowledgefrom ESPRIT project (some folks on this list worked on it)https://pdfs.semanticscholar.org/193e/b66909b0c87d5dbcdbd6b20d78ed93fc95a7.pdf  

 I d be curious to learn when such term knowledge graph came in use and who coined it 
I then heard it in relation to the SW and this list, and always tried to figure out what exactly a KG is (in relation the wider Knowledge Representation domain I was studying)
Knowledge graphs are a type of knowledge representation, and they can be visualizedgraphically, or represented using algebra (again, depends on what planet you are on)Engineers tend to use diagrams, others tend to use algebra
But more importantly, is that they enable machine readability querying and computational manipulation of complex (combined) data sets, assuming knowledge is some kind of data in context, as some say.I dont use the term knowledge graph much either.  Let's see if the KG folks can offer more info
PDMKnowledge Graph RepresentationKnowledge graphs provide a unified format for representing knowledge about relationships between entities. A knowledge graph is a collection of triples, with each triple (h,t,r) denoting the fact that relation r exists between head entity h and tail en- tity t. http://ceur-ws.org/Vol-2322/dsi4-6.pdf 
 




On Thu, Jun 13, 2019 at 1:40 PM 我 <1047571207@qq.com> wrote:

Dear all:
When I first touch knowledge graph, I'm very confused. Different from the other AI theory,  it is not an pattern recognization algorithm which will  give some "output" given some "input"(such as classify algorithms) ,but a program language(such as owl,rdf) and database(such as neo4j) instead. So in my opinion, knowledge graph is more like a problem of engineering than mathematic theory.  
Then I realized that different from the pattern recognization algorithm, the knowledge graph is created aimed at making the computes all over the world to  communicate with each other with a common language, and I have a question: Is scalability the key property of knowledge graph?
There are many knowledge vaults edited by different language(such as owl,rdf ),but is it always hard to merge them and there is not a standard knowledge vault  on which  we can do advanced  development. So is it necessary to open a scalable  and standard knowledge vault so that everyone can keep extended it and make it more perfect just like linux kernel or  wiki pedia? What kind of knowledge should be contained in the standard knowledge vault so that it can be universal?  I imagine that the standard knowledge vault is an originator, and all of the other application copy the originator, then all of the other application can communicate under the same common sense, for example when a application decelerate ''night", all of the other application will know it's dark. 
As I know, the knowlege graph is implement as a query service, but is it possible to implement it  as a program language,just like c++,java? In this way ,the compute can directly know nature language, and human can communicate with compute with nature language, also a compute can communicate with another compute with nature language.













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Regards

Chris
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Chief Executive, Lacibus Ltd
chris@lacibus.net