Ontotext

MARCH 13, 2024

Eventually, this led to the transformation of the project into forming an expansive knowledge graph containing all the marketing knowledge we’ve generated, ultimately benefiting the whole organization. OTKG models information about Ontotext, combined with content produced by different teams inside the organization.

Marketing 72

Marketing Knowledge Discovery Metadata Data-driven 72

Rocket-Powered Data Science

JULY 6, 2021

Techniques that both enable (contribute to) and benefit from smart content are content discovery, machine learning, knowledge graphs, semantic linked data, semantic data integration, knowledge discovery, and knowledge management. Collect, curate, and catalog (i.e.,

Strategy 266

Strategy Machine Learning Metadata Knowledge Discovery 266

Ontotext

APRIL 6, 2023

Knowledge graphs are changing the game A knowledge graph is a data model that uses semantics to represent real-world entities and the relationships between them. It can apply automated reasoning to extract further knowledge and make new connections between different pieces of data. standards modeled in a knowledge graph!

Manufacturing 83

Manufacturing Cost-Benefit Knowledge Discovery Optimization 83

Ontotext

DECEMBER 1, 2023

Seen through the three days of Ontotext’s Knowledge Graph Forum (KGF) this year, complexity was not only empowering but key to the growth of knowledge and innovation. If we want to understand and describe how things work and relate, unambiguously exchange data, or reuse it, we need a semantic data model.

Metadata 78

Metadata Sales Consulting Enterprise 78

Ontotext

AUGUST 15, 2019

In order to feel comfortable and keep up with the training, participants need to have at least a basic understanding of the SPARQL query language and the underlying graph-based data model. As always, the most convincing is to see how the knowledge gained from our training can lead to a successful solution. Want to see for yourselves?

Knowledge Discovery 70

Knowledge Discovery Technology Metadata Interactive 70

Data Science 101

OCTOBER 31, 2019

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). The models created using these algorithms could be evaluated against appropriate metrics to verify the model’s credibility. Data Mining Models. Classification.

Data mining 77

Data mining KDD Data Science Forecasting 77

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. Create a human AND machine-meaningful data model.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69