Improved Content Discoverability

Improve the discoverability of your content by creating rich metadata, centered around the meaning of concepts and their relationships. Advanced search paradigms are enabled through content enrichment. We achieve this by employing semantic technology techniques for retrieving knowledge from richly structured data sources and making better sense of the user’s intent and the query context.

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How You’ll Benefit

Enhance the discoverability of your content
Optimize your editorial efforts and facilitate enhanced cooperation
Organize your content for relevant navigation and exploration

How it Works

From strings to things

Knowledge graph based search enables you to search for things (people, places, organizations, events, etc.) and the relationships between them, instead of strings (just keywords). Such an advanced search offers more comprehensive breadth and depth, and instantly provides information that is relevant to your query. 

Semantically typed data

The ability to assign an instance to a defined class (i.e., Person, Organization, Location) allows you to narrow down and increase the relevance of your search results. For example, searching for “Washington” among people may return former presidents, in locations – cities, and in organizations – sports teams.

Ranking of results

Based on knowledge graph connectivity and structural similarity, our advanced search sorts through tons of content to present the most relevant results. Search algorithms take many factors into consideration and assign them different weights depending on your use case.

Graph embeddings and graph similarity

Full-text indexes can be only good where there is a string matching similarity. GraphDB provides the ability to index content through embeddings or to uncover similarity on the basis of the underlying graph structures. Combined with full-text search and ranking, graph embeddings provide additional paradigms to uncover potentially relevant results.


Modern systems are expected to be used simultaneously by hundreds or even thousands of users. Traditional databases are not well suited to serve such loads and always impose a compromise between the key requirements of freshness, scalability and speed, at a manageable cost. 

Discovery paradigms

  • Search – enable advanced search paradigms that filter out unwanted results and return relevant results faster.
  • Navigate – create rich navigation options enabling users to get easy access to web pages.
  • Recommend – improve personalization, search experience and discoverability.

Case Studies

News on the Web (NOW)

A free public service, showcasing the opportunities open up before media and publishing companies. Get a real feel of the world where semantic technologies are already shaping the way we search, discover and consume content.

Products, Solutions and Services Involved

Ontotext Metadata Studio


Text Analysis for Content Management

Knowledge Graph Enrichment