Re: Is scalability the key property of knowlege graph?

Dieter,
correct. In this sense, technically the raison d'être of KGs is the good old problem of data integration.
Where you trade, in order to tackle the scalability problem, the rich semantics of the original distributed structured databases with the flexibility and approximate semantics of distributed KGs.
--e.

Il giorno 14 giu 2019, alle ore 22:13, Dieter Fensel <dieter.fensel@sti2.at<mailto:dieter.fensel@sti2.at>> ha scritto:


Yes, but it is the size that makes them different from semantic net stuff. No longer 10,000 facts but frillions of triples that are distributed, heterogeneous, inconsistent, out of date and change faster as you can reason about them. So in an abstract sense they are the same and in concrete terms they come with very different requirements.

On 13.06.2019 15:49, Franconi Enrico 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<mailto: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<mailto: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 turn
depends on the domain (which planet you come from)

When I first studied knowledge engineering, the expression knowledge graph
was not in use at all. I was doing an MSc and studied the body of knowledge
from 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 visualized
graphically, 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

PDM
Knowledge Graph Representation
Knowledge 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<mailto: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.











--
Regards

Chris
++++

Chief Executive, Lacibus<https://lacibus.net/> Ltd
chris@lacibus.net<mailto:chris@lacibus.net>



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