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. Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Ontotext

AUGUST 19, 2020

XML and later JSON were the languages that enabled data interchange by establishing a common data model by establishing a standard description of the data being shared. Beyond the ability to ensure there was an enterprise wide data model, it was also possible to reuse data but with different metadata and schema.

Metadata 59

Metadata Knowledge Discovery Cost-Benefit Data Governance 59

Domino Data Lab

MAY 20, 2021

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. Data mining for direct marketing: Problems and solutions. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. 30(2–3), 195–215. link] Ling, C.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

Ontotext

AUGUST 31, 2023

The growth of large language models drives a need for trusted information and capturing machine-interpretable knowledge, requiring businesses to recognize the difference between a semantic knowledge graph and one that isn’t—if they want to leverage emerging AI technologies and maintain a competitive edge.

Modeling 64

Modeling Knowledge Discovery Optimization Enterprise 64

Ontotext

AUGUST 16, 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. You should also keep in mind that more and more reports estimate that until 2022 the annual growth of the graph database market will be 100%.

Knowledge Discovery 40

Knowledge Discovery Technology Metadata Interactive 40

Ontotext

FEBRUARY 21, 2024

RAG and Ontotext offerings: a perfect synergy RAG is an approach for enhancing an existing large language model (LLM) with external information provided as part of the input prompt, or grounding context. So we have built a dataset using schema.org to model and structure this content into a knowledge graph.

Knowledge Discovery 64

Knowledge Discovery Technology Metadata Data-driven 64

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

“We have just emerged from a terrible recession called New Year's Day where there were very few market transactions,” joked Hal Varian, Google’s Chief Economist, recently. Doing so makes it easier to study the effects of an intervention, say, a new marketing campaign, on the sales of a product.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

CIO Business Intelligence

MARCH 26, 2025

The combination of AI and search enables new levels of enterprise intelligence, with technologies such as natural language processing (NLP), machine learning (ML)-based relevancy, vector/semantic search, and large language models (LLMs) helping organizations finally unlock the value of unanalyzed data. How did we get here?

Knowledge Discovery 84

Knowledge Discovery Cost-Benefit Enterprise Technology 84