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Re: [ontolog-forum] Regarding Neo4j for Ontology

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: Duane Nickull <duane@xxxxxxxxxxx>
Date: Tue, 24 Apr 2012 14:28:42 +0000
Message-id: <CBBC05C7.F0BD7%duane@xxxxxxxxxxx>
Peter:    (01)


Thank you so much for eloquently stating my original statement, albeit far
better.    (02)

I have been in this forum for over a decade and neo4J really excites me as
the traversal model really nails a lot of use cases for inference and
reasoning.  I especially love the ability to set the depth of traversals
for limits which matches the old school AI Blackboard pattern very well
when it come to building several hypothesis, holding the stores in tuples,
analyzing, then moving to further traversals with the highest weighted
hypothesis.    (03)

I am thinking of a project to embark on to illustrate this and document it.    (04)

Best wishes    (05)

Duane Nickull    (06)

******************    (07)

COO and Director 
Uberity Technology Corporation
"LiveCycle ES and Mobile Specialists"
http://www.uberity.com
@uberity @duanechaos    (08)


On 12-04-24 3:01 AM, "Peter Neubauer" <peter.neubauer@xxxxxxxxxxxxxxxxx>
wrote:    (09)

>Hi all,
>Dan just pointed me to this discussion, I just wanted to provide a bit
>of input here.
>
>Yes, Neo4j is not trying to do indexing. For that, you use whatever
>suits best, like Lucene, SOLR, Redis ... we combine that with local
>traversal which Neo4j IS good at. So, IMHO this is slightly off the
>point - it's the combination of the graph traversal and the index
>lookups that give you the maximum performance. This has proven to be
>very effective in a number of domains, since you by choosing the right
>tool (index lookups, traversals or raw memory-operations) have a
>number of degrees of freedom to get maximum performance.
>
>Cheers,
>
>/peter neubauer
>
>G:  neubauer.peter
>S:  peter.neubauer
>P:  +46 704 106975
>L:   http://www.linkedin.com/in/neubauer
>T:   @peterneubauer
>
>If you can write, you can code - @coderdojomalmo
>If you can sketch, you can use a graph database - @neo4j
> 
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>    (010)



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