Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). So, there must be a strategy regarding who, what, when, where, why, and how is the organization’s content to be indexed, stored, accessed, delivered, used, and documented. Smart content includes labeled (tagged, annotated) metadata (TAM).

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

Ontotext

AUGUST 19, 2020

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.

Metadata 59

Metadata Knowledge Discovery Cost-Benefit Data Governance 59

Ontotext

MARCH 13, 2024

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.

Marketing 72

Marketing Knowledge Discovery Metadata Data-driven 72

Ontotext

JULY 29, 2021

Knowledge graphs (KG) came later, but quickly became a powerful driver for adoption of Semantic Web standards and all species of semantic technology implementing them. This way KGs help organizations smarten up proprietary information by using global knowledge as context for interpretation and source for enrichment.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

AWS Big Data

SEPTEMBER 26, 2024

Organizations are collecting and storing vast amounts of structured and unstructured data like reports, whitepapers, and research documents. End-users often struggle to find relevant information buried within extensive documents housed in data lakes, leading to inefficiencies and missed opportunities.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

Ontotext

MARCH 8, 2023

Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Ontotext

FEBRUARY 21, 2024

So we can easily integrate the information from both textual documents and structured RDF entities into an LLM-driven application. Example use case: Ontotext Knowledge Graph For illustration, we will use a project developed internally by Ontotext that we call “Ontotext Knowledge Graph” or OTKG for short.

Knowledge Discovery 64

Knowledge Discovery Technology Metadata Data-driven 64