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). Also known as outlier detection, anomaly detection is an unsupervised learning technique that is used to find rare occurrences or suspicious events in your data.

Data mining 77

Data mining KDD Data Science Knowledge Discovery 77

Ontotext

JULY 29, 2021

We rather see it as a new paradigm that is revolutionizing enterprise data integration and knowledge discovery. Providing a formal unified conceptual model, ontologies enable unified access to and correct interpretation of diverse information and greatly facilitate analytics, decision making and knowledge re-use.

Enterprise 124

Enterprise Metadata Knowledge Discovery Management 124

Ontotext

APRIL 6, 2023

This delivers greater visibility to product movement and tracking events throughout the whole supply chain, for fostering interoperability and transparency. To Wrap It Up Knowledge graphs play a vital role in connecting the data from siloed legacy systems and platforms, enabling seamless data sharing, knowledge discovery and analytics.

Manufacturing 83

Manufacturing Cost-Benefit Knowledge Discovery Optimization 83

Domino Data Lab

MAY 20, 2021

A rule-learning program in high energy physics event classification. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. Smote: Synthetic minority over-sampling technique. 16(1), 321–357. Clearwater, S., & Stern, E. Computer Physics Communications, 67(2), 159–182. link] Ling, C.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

Ontotext

DECEMBER 1, 2023

Seen through the three days of Ontotext’s Knowledge Graph Forum (KGF) this year, complexity was not only empowering but key to the growth of knowledge and innovation. Knowledge graphs are often criticized for being too complex”, said Atanas, “but such initiatives actually are bound to be complex.

Metadata 78

Metadata Sales Machine Learning Consulting 78

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. It is also better interconnected, which brings more content and enables deeper analytics.

Metadata 69

Metadata Knowledge Discovery Data Quality Data-driven 69

Ontotext

AUGUST 16, 2019

As always, the most convincing is to see how the knowledge gained from our training can lead to a successful solution. The aim of this project is to make cultural events findable for voice-powered and AI-powered search assistants. One of the best success stories as a result of our training is Culture Creates.

Knowledge Discovery 40

Knowledge Discovery Technology Metadata Interactive 40

Ontotext

APRIL 4, 2019

We minimized the time between the event (and what the journalist wanted to say about it) and the moment the reader or viewer could consume it. Economy.bg: What about journalists? Milena Yankova : What we did for the BBC in the previous Olympics was that we helped journalists publish their reports faster.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

The Unofficial Google Data Science Blog

JANUARY 14, 2016

In any event, let’s say we have an appropriate choice of experimental unit. As the event becomes rarer, this grows as $1/sqrt{p}$. Sometimes, the metric of interest is not the average rate of a rare binary event, per se, but is gated by such an event.

Experimentation 42

Experimentation Statistics Metrics Measurement 42

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

Rare binary event example In the previous post , we discussed how rare binary events can be fundamental to the LSOS business model. Let $Y$ be the Bernoulli random variable representing the purchase event in a user session. Y$ is the binary event of a purchase. To that end, it is worth studying them in more detail.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

Ontotext

NOVEMBER 11, 2024

Knowledge Graphs Defined and Why Semantics (and Ontologies) Matter According to Wikipedia , a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data.

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52