Data-driven Document Knowledge Discovery Metadata 
Ontotext
MARCH 13, 2024
We started with our marketing content and quickly expanded that to also integrate a set of workflows for data and content management. Our goal is to generate a knowledge space where information is easy to find, reuse, and fuel knowledge-driven insights. The behind-the-scenes interface Let’s see how this works.
Rocket-Powered Data Science
JULY 6, 2021
Specifically, in the modern era of massive data collections and exploding content repositories, we can no longer simply rely on keyword searches to be sufficient. This is accomplished through tags, annotations, and metadata (TAM). Contextual TAM enhances a CMS with knowledge-driven search and retrieval, not just keyword-driven.
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Ontotext
MARCH 8, 2023
Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Several factors are driving the adoption of knowledge graphs. Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions.
Ontotext
JULY 29, 2021
The Semantic Web, both as a research field and a technology stack, is seeing mainstream industry interest, especially with the knowledge graph concept emerging as a pillar for data well and efficiently managed. And what are the commercial implications of semantic technologies for enterprise data? Source: tag.ontotext.com.
Ontotext
FEBRUARY 21, 2024
This is part of Ontotext’s AI-in-Action initiative aimed at enabling data scientists and engineers to benefit from the AI capabilities of our products. Natural Language Query (NLQ) has gained immense popularity due to its ability to empower non-technical individuals to extract data insights just by asking questions in plain language.
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