GraphDB 8.9 with Improved Semantic Similarity Search


9 Apr 2019


Sirma Group

Sirma AI has launched a new version of its signature semantic graph database - GraphDB. The new release offers a number of features, requested by users, providing feedback for further improvements.

The latest GraphDB enables users to create hybrid similarity searches using pre-built text-based similarity vectors for the predication-based similarity index. The index combines the power of graph topology with the text similarity. The index accuracy can be controlled by users, specifying the number of iterations required to refine the embeddings.

Another new feature, offered by the new version 8.9., is enabling users to boost the term weights when searching in text-based similarity indexes. It also simplifies the processes of termination of running queries or updates from the SPARQL editor in the Workbench.

Read the news and learn more about GraphDB.