Ontotext

AUGUST 26, 2021

The second Ontotext webinar Graph Analytics on Company Data and News focuses on the power of cognitive graph analytics to create links between various datasets and to lead to powerful knowledge discovery.

Analytics 52

Analytics Knowledge Discovery Enterprise Optimization 52

Ontotext

DECEMBER 30, 2019

As 2019 comes to an end, we at Ontotext are taking stock of the most fascinating things we have done to empower knowledge management and knowledge discovery this year. In 2019, Ontotext open-sourced the front-end and engine plugins of GraphDB to make the development and operation of knowledge graphs easier and richer.

Knowledge Discovery 52

Knowledge Discovery Publishing Technology Enterprise 52

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. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. 30(2–3), 195–215. link] Ling, C. X., & Li, C. Quinlan, J. Programs for machine learning.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

The Unofficial Google Data Science Blog

JULY 22, 2020

Companies like Google [2], Amazon [3], and Microsoft [4] have all published scholarly articles on this topic. Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

TDAN

JUNE 15, 2022

“Information is the oil of the 21st century, and analytics is the combustion engine,” says Peter Sondergaard, former Global Head of Research at Gartner. And he has a point. Given that the global big data market is forecast to be valued at $103 billion in 2027, it’s worth noticing. As the amount of data generated […].

Data mining 98

Data mining Big Data Forecasting Marketing 98

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

Domino Data Lab

JUNE 15, 2021

Although in this article we focused on one-way use-cases (i.e. This facilitates knowledge discovery, handover, and regulatory compliance, and allows the individual data scientists to focus on work that accelerates research and speeds model deployment. About Domino.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. Conference on Knowledge Discovery and Data Mining, pp. Ribeiro, M. Guestrin, C., Why should I trust you?:

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139