Remove Blog Remove Knowledge Discovery Remove Metadata
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Ontotext Marketing Gets a Boost from Knowledge Graph Powered LLMs

Ontotext

We store this in GraphDB by leveraging standard tooling for knowledge graph management. Through Ontotext Metadata Studio (OMDS), we then apply semantic content enrichment using text analysis based on our marketing vocabularies. In this way, we benefit from better SEO and semantic-driven content discovery.

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Three’s Company Too: Metadata, Data and Text Analysis

Ontotext

Metadata used to be a secret shared between system programmers and the data. Metadata described the data in terms of cardinality, data types such as strings vs integers, and primary or foreign key relationships. Inevitably, the information that could and needed to be expressed by metadata increased in complexity.

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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

If you include the title of this blog, you were just presented with 13 examples of heteronyms in the preceding paragraphs. This is accomplished through tags, annotations, and metadata (TAM). Smart content includes labeled (tagged, annotated) metadata (TAM). What you have just experienced is a plethora of heteronyms.

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Knowledge Graphs 101: The Story (and Benefits) Behind the Hype

Ontotext

Knowledge graphs, while not as well-known as other data management offerings, are a proven dynamic and scalable solution for addressing enterprise data management requirements across several verticals. As a hub for data, metadata, and content, they provide a unified, consistent, and unambiguous view of data scattered across different systems.

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Why Establishing Data Context is the Key to Creating Competitive Advantage

Ontotext

Without metadata management and other data-related operations with semantic technologies, organizations often struggle to connect data sets and achieve a unified view of their enterprise data. Enter the Semantic Edge Era: How to Derive Value from Semantic Metadata The problem with Big Data is not the data itself.

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On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. Again, the overall aim is to extract knowledge from data and, through algorithms based on artificial intelligence, to assist medical professionals in routine diagnostics processes.

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From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

This means the creation of reusable data services, machine-readable semantic metadata and APIs that ensure the integration and orchestration of data across the organization and with third-party external data. Knowledge Graphs are the Warp and Weft of a Data Fabric. This provides a solid foundation for efficient data integration.