In the not too distant past, analysts were all searching for a “360 degree view of their data”. Most of the time this phrase referred to integrated RDBMS data, analytics interfaces and customers. But with the onslaught of
The Ontotext GraphDB™ (formerly OWLIM) development team integrated the LDBC Semantic Publishing Benchmark (LDBC-SPB) into the development and release process. In this blog post, available on the Linked Data Benchmark Council web
The first webinar about the Self-Service Semantic Suite (S4) will take place on Feb 26th (11am EST / 8am PST / 4pm GMT). Featuring Ontotext CTO, Marin Dimitrov, the webinar will provide a brief technical introduction to the S4 cap
A couple of weeks ago Ontotext released a version of its GraphDB™ Standard triplestore (RDF database) on the AWS cloud, as part of the Self-Service Semantic Suite (S4) commitment to provide easy, on-demand and pay-per-use acc
Last week I had a chance to present the Self Service Semantic Suite (S4) at the LT-Accelerate conference in Brussels. LT-Accelerate is a new event focusing on language technology and its applications in various domains: social med
The Self-Service Semantic Suite (S4) by Ontotext provides a set of capabilities for on-demand, as-a-service semantic data management. The S4 capabilities are accessible via simple RESTful APIs, including APIs for tex
Getting started with S4, The Self-Service Semantic Suite is as easy as registering for a developer account and accessing RESTful services for text analysis and linked data querying.
Here's how S4 developers can get started with T
Text Mining in the Cloud - Enterprise Technology for the Mid Market
If you thought that enterprise semantic technology was just for Fortune 2000 companies, think again. The very same semantic technology is now available in the Am
Text Mining and Graph Databases work well together because natural language processing can be used to extract meaning from free flowing text and then stored in graph databases to be used in search, discovery and analysis.