What Is the DIKW Pyramid? | Ontotext Fundamentals
The DIKW Pyramid represents the relationships between data, information, knowledge, and wisdom, adding value to the initial data.| Ontotext
The DIKW Pyramid represents the relationships between data, information, knowledge, and wisdom, adding value to the initial data.| Ontotext
Semantic Search helps optimize the accuracy of the results and makes them highly contextual and personalized.| Ontotext
How ontologies introduce a sharable and reusable knowledge representation and add new knowledge about a domain.| Ontotext
Semantic metadata enriches data by adding references to concepts in a knowledge graph, making it easier to find, use, and manage.| Ontotext
Machine learning is about teaching computer programs to recognize images, words and sounds by giving them a lot of examples to learn from| Ontotext
LLMs are deep learning models that learn patterns and relationships from large volumes of textual data in order to generating new text| Ontotext
Semantic Technology, unlike other technologies, deals with the meaning rather than the structure of the data.| Ontotext
How enterprises can reorient their approach to data management and reduce bad data tax by adopting a graph based semantic thinking.| Ontotext
PubMiner AI aims to help researchers in the biomedical domain overcome the challenges in automatic knowledge extraction from large volumes of scientific publications. The post Advancing Automatic Knowledge Extraction with PubMiner AI appeared first on Ontotext.| Ontotext
How we used Ontotext GraphDB and LLMs to improve CV selection The post Speeding Up Cancer Research with Target Discovery: An Interview with a Global Top 10 Early Drug R&D Center appeared first on Ontotext.| Ontotext
LLD Inventory forms the semantic foundation for Ontotext’s Target Discovery solution. The post Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery appeared first on Ontotext.| Ontotext
Read this post providing a guide for deploying an Ontotext GraphDB high-availability cluster in your own AWS account The post Deploying Ontotext GraphDB on AWS appeared first on Ontotext.| Ontotext
Read about three GraphDB-powered use cases in the areas of machine learning, software engineering, and e-health, which are poised to move our understanding and practices of interconnectedness forward by using semantic technologies. The post GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains appeared first on Ontotext.| Ontotext
Ontotext's Tag service can recognize entities and assign standard identifiers that let you enrich your graphs. The post Using Entity Linking to Turn Your Graph into a Knowledge Graph appeared first on Ontotext.| Ontotext
Read about how How a Graph Center of Excellence can help businesses achieve their strategic goals using a small-scale pilot initiative that serves as a model for other similar projects The post Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success appeared first on Ontotext.| Ontotext
Guillaume Rachez, VP of Product at Perfect Memory, talks with Doug Kimball about why knowledge graphs offer the most efficient access to information.| Ontotext
An abbreviated and updated version of a presentation from Knowledge Graph Forum 2023 by Eban Tomlinson, Director of Sales and Marketing at Semaphore| Ontotext
Learn about semantic web standards and knowledge graph application development for free with Ontotext Academy.| Ontotext
An abbreviated and updated version of a presentation from Ontotext’s Knowledge Graph Forum 2023 by René Pietzsch, Product Manager at eccenca| Ontotext
Learn from Martin Trajkov, Biz Dev and Partner Sales Engineer at Semantic Web Company about Enterprise PowerPack| Ontotext
Knowledge graphs are a collection of interlinked descriptions of entities that put data into context and enable data analytics & sharing.| Ontotext
