Ever since the introduction of the Google Knowledge Graph, a growing number of organizations have adopted this powerful technology to drive efficiency and effectiveness in their data management ...

Knowledge graphs serve as the system of intelligence layer to build smarter, more accurate and grounded agents, turning data into actions that drive business outcomes in agentic AI workflows.

The goal of knowledge discovery in databases (KDD) is the (semi)-automatic extraction of implicit, valid and potentially useful knowledge from these databases. The core step of KDD, which has received ...

Generative AI depends on data to build responses to user queries. Training large language models (LLMs) uses huge volumes of data—for example, OpenAI’s GPT-3 used the CommonCrawl data set ...

By integrating with Databricks, customers can use the Altair RapidMiner knowledge graph engine to connect, contextualize, and activate all types of data—structured, unstructured, and streaming.

It involves understanding metadata knowledge graphs and how different layers of the modern data stack come together. If one wants to do anything with data, they need a stack of tools to get it done.

It also provides a case study illustrating the use of LLMs as knowledge graphs for data mining in general. Journal. Quantitative Biology. DOI. 10.1002/qub2.57 . Method of Research.