Sparql

Finding Fraud, Part Two

Finding Fraud, Part Two

Paul Jackson

Unify data at query time using Stardog to make fraud detection more dynamic.

Aug 25, 2018

Studio Gets Smart

Studio Gets Smart

The Studio Team

We’re happy to announce the release of Stardog Studio v0.3.0, the first version of Studio to include advanced language intelligence capabilities for SPARQL and Stardog SPARQL extensions.

Jun 29, 2018

Finding Fraud with Stardog

Finding Fraud with Stardog

Paul Jackson

Let’s see how we can use the Knowledge Graph to detect fraud in financial services.

May 1, 2018

Easy Graph is Good Graph

Easy Graph is Good Graph

Jess Balint

Stardog 5.2.2 makes it drop dead easy to use named entity recognition and linking and to map RDBMS silos into the graph.

Mar 7, 2018

Fixing Avoidably Slow Queries

Pavel Klinov

Unselective Queries First, let’s consider unselective queries, that is, those which return large result sets and are often user errors. In the worst case an unselective query is indistinguishable from a bulk data transfer over a highly inefficient mechanism. Here’s a simplified version of one such query that we saw recently: CONSTRUCT { ?bus a :Bus . ?tram a :Tram . } WHERE { ?bus rdfs:label ?busLabel. FILTER (CONTAINS(LCASE(?busLabel), "bus")) ?

May 23, 2017

Avoidably Slow Queries

Avoidably Slow Queries

Pavel Klinov

This is an appendix to 7 Steps to Fast SPARQL Queries.

May 23, 2017

7 Steps to Fast SPARQL Queries

7 Steps to Fast SPARQL Queries

Pavel Klinov

You want SPARQL queries in Stardog to be as fast as possible. And we know all the secrets. All you have to do is read.

May 23, 2017

How to Read Stardog Query Plans

Pavel Klinov

Our mission is to unify all enterprise data in a single, coherent graph managed by Stardog. Like many database systems Stardog answers queries in two major phases: determining the query plan and executing that plan to obtain answers from the data.

Jan 3, 2017

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