It's the semantic web.
For inference, see http://www.w3.org/standards/semanticweb/inference
Materialization is the pre-computation and storage of inferred triples
http://www.w3.org/wiki/LargeTripleStores
In fact, I use JSON-LD, which is convenient for both storing triples and
loading them for se
Hi Jörg,
The assumptions you've made on my use case are correct.
The nightly update could definitely work, but I think even live updates
could work as the data is quite static in nature.
A few more questions:
* You're talking about recreation of the index, with this you mean update I
presume?;
I'm not sure, and I try hard to understand your use case.
I assume you want a single query that can filter attributes of both the
entity "1" and for attributes of related entities "2" and "3".
As you have noticed, in a single query, this is not possible unless you had
"bubbled up" the relevant at
Hi Jörg,
Thank you for your answer. Lots of new stuff in there though which will
require some studying to understand :) !
JSON-LD seems like an excellent addition to JSON which could actually mean
some competition for graph databases?!
I've tried to setup the following simple 2 dispenser, 2 disp
I am using JSON-LD, which boils down to something like this
{
...
"_source" : {
"@context" : { "rel" : "..." },
"@id" : 476,
"@type" : " ",
"description" : "Product description",
"a8" : "100 mm",
"a12" : "250 g",
Hi,
We are using ElasticSearch for navigating through our product catalog. We
have fairly simple documents like:
{
"_index": "catalog",
"_type": "product",
"_id": "476",
"_score": 1,
"_source": {
"id": 476,
