Ontotext Blog

Using LDBC-SPB to Find OWLIM (GraphDB™) Performance Issues

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

S4 Webinar: “Text Mining and Knowledge Graphs in the Cloud”

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

RDF Data Management in the Cloud with GraphDB™

GraphDB Cloud on AWS
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

On-demand Metadata Management with Ontotext S4

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

GATE and Firefox plugins for S4

Gate Firefox header
Introduction 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

Self Service Semantic Suite
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: Ontotext Releases “S4” – The Self Service Semantic Suite

Text mining in the cloud
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 & Graph Databases – Two Technologies that Work Well Together

Text Mining, graph databases and ontologies expand your search
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. Graph

Semantic Publishing – Relevant Recommendations Create a Unique User Experience

Semantic recommendations is part of semantic publishing technology
Semantic Publishing includes a number of techniques including semantic recommendations used to personalize the user experience by delivering contextual content based on natural language processing, search history, user profiles an

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