Making Sense of Text and Data
Provide consistent unified access to data across different systems by using the flexible and semantically precise structure of the knowledge graph model
Interlink your organization’s data and content by using knowledge graph powered natural language processing with our Content Management solutions.
Implement a Connected Inventory of enterprise data assets, based on a knowledge graph, to get business insights about the current status and trends, risk and opportunities, based on a holistic interrelated view of all enterprise assets.
Quick and easy discovery in clinical trials, medical coding of patients’ records, advanced drug safety analytics, knowledge graph powered drug discovery, regulatory intelligence and many more
Make better sense of enterprise data and assets for competitive investment market intelligence, efficient connected inventory management, enhanced regulatory compliance and more
Connect and model industry systems and processes for deeper data-driven insights in:
- Manufacturing
- Automotive Industry
- Energy
- Building Automation
- Infrastructure
- Aerospace & Defense
Improve engagement, discoverability and personalized recommendations for Financial and Business Media, Market Intelligence and Investment Information Agencies, Science, Technology and Medicine Publishers, etc.
Unlock the potential for new intelligent public services and applications for Government, Defence Intelligence, etc.
Connect and improve the insights from your customer, product, delivery, and location data. Gain a deeper understanding of the relationships between products and your consumers’ intent.
Link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.
Organize your information and documents into enterprise knowledge graphs and make your data management and analytics work in synergy.
Integrate and evaluate any text analysis service on the market against your own ground truth data in a user friendly way.
Turn strings to things with Ontotext’s free application for automating the conversion of messy string data into a knowledge graph.
KGF 2021 Talks: Graph Path Search with GraphDB
This talk was presented by Tomas Kovachev, Software engineer lead at Ontotext, at the Ontotext and Partners Knowledge Graph Forum in October 2021.
Knowledge graphs have become a popular trend in the representation of complex data, metadata and content. Search and graph exploration are key tools for successfully utilizing knowledge graphs.
In this talk, Tomas Kovachev, Software engineer lead at Ontotext, explains why graph path search is a computationally expensive task and presents our graph path search implementation. He compares how the different RDF and property graph databases implement it and dives into how GraphDB extends the SPARQL 1.1 standard to fully support all significant graph path search use cases.