The Ontotext Dynamic Semantic Publishing Platform consists of a set of databases, machine learning algorithms, APIs and tools we use to build solutions for news, educational, scientific, academic and other publishers.
At a high level, the platform consists of:
With 32 teams, 8 groups and 776 individual players, managing the Web site for the 2010 FIFA World Cup was a daunting task. There were simply too many pages and too few journalists too many pages and too few journalists to create and manage the site’s content.
After growing in part through acquisition, Euromoney found itself with 84 brands and more than 100 different publications. They turned to Ontotext for a solution that would help them easily reuse and repurpose content within and between the business units.
Ontotext Dynamic Semantic Publishing platform leverages a variety of data sources to deliver optimal results. At the heart of the solution is a knowledge base used to classify all of your content and metadata. This is combined with your content store, Linked Open Data for enrichment and profiles tracking behavior over time. This blend of semantic databases is stored and accessible from our graph databases engine, GraphDB™.
Engage Your Readers with Personalized Adaptive Content Ontotext Semantic News Publishing is the basis of our solutions in news & media publishers.
Ontotext Scientific Publishing helps publishers maximize content value by leveraging existing taxonomies, thesauri and controlled vocabularies.
Ontotext Personalized Learning harnesses semantic technology to empower educators. Educators can match student needs with relevant learning resources.
Users are able to search content using key words, phrases, facets and full text search. Behind the scenes we build hybrid queries, powerful SPARQL that queries your content store and the GraphDB™ RDF triplestore simultaneously. We don’t compromise performance in production environments that have large volumes of queries, updates and inferences taking place on the database at the same time.
By using semantic knowledge, your internal users and website visitors see the most important and relevant content. This creates a very powerful, compelling user experience leading to higher levels of loyalty and dramatic improvements in authoring time.
Users are able to search content using key words, phrases, facets and full text search.
Our text mining pipelines analyze your text, extract concepts, identify important entity relationships, classify all of your content and disambiguate entities that are similar.
We are able to ingest and normalize content and data from any number of diverse sources.
As users work with the system, Ontotext Dynamic Semantic Publishing platform is constantly learning, remembering and refining responses.
We have combined user profiles, search histories and semantic classifications of data to deliver hyper-contextual results.