Ontotext

NOVEMBER 22, 2024

It also facilitates retrieval from a highly targeted subset of documents containing relevant information for the particular use case. Finally, it enables building a subgraph representing the extracted knowledge, normalized to reference data sets.

Knowledge Discovery 52

Knowledge Discovery Visualization Data-driven Data Processing 52

Ontotext

MARCH 4, 2020

First of all, this solution is able to ingest large amounts of various documents in various formats and to automatically extract and classify pairs of questions and answers. It represents the relationships between the different elements of the document and empowers a semantic search. The Power of Semantic Text Similarity.

Knowledge Discovery 52

Knowledge Discovery Manufacturing Finance Technology 52

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 114

Data Lake Cost-Benefit Unstructured Data Modeling 114

Ontotext

JULY 29, 2021

In more detail, they explained that just as the hypertext Web changed how we think about the availability of documents, the Semantic Web is a radical way of thinking about data. We rather see it as a new paradigm that is revolutionizing enterprise data integration and knowledge discovery.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Ontotext

APRIL 6, 2023

There is an overwhelming amount of standardization efforts and reference initiatives, which double down on the benefit from the knowledge graph approach. standards modeled in a knowledge graph! Here again knowledge graphs organize and link large amounts of data on aircraft design, manufacturing, maintenance and performance.

Manufacturing 83

Manufacturing Cost-Benefit Knowledge Discovery Optimization 83

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 former is a term used for models where the data has been labeled, whereas, unsupervised learning, on the other hand, refers to unlabeled data. Classification. Common Applications.

Data mining 77

Data mining KDD Data Science Forecasting 77

Domino Data Lab

DECEMBER 4, 2020

The openness of the Domino Data Science platform allows us to use any language, tool, and framework while providing reproducibility, compute elasticity, knowledge discovery, and governance. References. [1] 2] Pumas AI Documentation, [link]. [3] 1] Gabrielsson J, Weiner D. Non-compartmental analysis. Methods Mol Biol.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59