Discussion Forum

Grakn application in transformational programming and source code analysis

Is anybody works with grakn in topics like transformational programming, MDA or automated code generation ?

I’m interested in this topics (just link to paper draft – only topics list in contents now), I would like to discuss about using hypergraph and grakn as core engine.

Other theme is knowledge representation and inference – also must be covered in paper and used in resulting system.
What resources should I read first as observing of grakn achievements in KB and expert systems design ?

PS: grak web interface look cool comparing to neo4j , I hope that capabilities of such a resource-heavy system corresponds to its appearance: my i7 workstation crouches on server start with empty database

Hi!
We have a few examples of Grakn being applied to modelling of expert systems/KB on our blog. For example
https://blog.grakn.ai/a-knowledge-graph-based-semantic-database-for-biomedical-sciences-167154319a0a

In general the way you model your domain is very similar to how you’d model things in E-R. If you have specific questions about the domain you are working on, feel free to ask here.

P.S. What do you mean by crouches on server start? We are working on reducing resource consumption but it would be interesting to get more detail on that.

What do you mean by crouches on server start?

Starting redis, cassandra and engine gives high load on processor and memory allocation, and has suprisingly long time comparing to neo4j starting. Not a problem, really, but gives impression of huge system.

If you have specific questions about the domain you are working on, feel free to ask here.

For example, is it possible to do some compiler-like application using grakn able to do ambiguity parsing (something like Prolog’s DCG grammar), and other compiler elements with structures vizualization using grakn’s standard tools ?