Domino Data Lab

MAY 20, 2021

We present the inner workings of the SMOTE algorithm and show a simple “from scratch” implementation of SMOTE. 2002) do not present a rigorous mathematical treatment for this modification, and the suggested median correction appears to be purely empirical-driven. A word of caution. Chawla et al. 30(2–3), 195–215.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

Ontotext

AUGUST 26, 2021

Here, we’ve decided to present another two Ontotext webinars that give the bird’s eye view of the enterprise knowledge graph technology we have dedicated 20+ years to develop for some of the most knowledge intensive enterprises in various industries. Both were presented by our CEO, Atanas Kiryakov.

Analytics 52

Analytics Knowledge Discovery Enterprise Optimization 52

AWS Big Data

SEPTEMBER 26, 2024

Automatic document summarization, natural language processing (NLP), and data analytics powered by generative AI present innovative solutions to this challenge. Surfacing relevant information to end-users in a concise and digestible format is crucial for maximizing the value of data assets.

Data Lake 115

Data Lake Cost-Benefit Unstructured Data Modeling 115

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

Recently, we presented some basic insights from our effort to measure and predict long-term effects at KDD 2015 [1]. References [1] Henning Hohnhold, Deirdre O'Brien, Diane Tang, Focus on the Long-Term: It's better for Users and Business , Proceedings 21st Conference on Knowledge Discovery and Data Mining, 2015. [2]

Modeling 63

Modeling Experimentation Knowledge Discovery KDD 63

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

The Unofficial Google Data Science Blog

JULY 22, 2020

Just as in ramp-up, making inferences while ignoring the complexity of time-based confounders that are present can lead to biased estimates. Thus we have conditional ignorability no matter how many time-based confounders are present. Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

Ontotext

AUGUST 19, 2020

Faster and easier knowledge discovery has obvious cost benefits and reduces duplication of effort. With good metadata and especially good semantic metadata, you are able to organize and present information more closely to how a human user understands it. More useful organization of information.

Metadata 59

Metadata Knowledge Discovery Cost-Benefit Data Governance 59

Ontotext

SEPTEMBER 15, 2020

Ontotext uses an automatically generated GraphQL API to support efficient integration into presentation layers. Start delivering the answers to your original questions through different knowledge discovery tools such as powerful SPARQL queries, easy to use GraphQL interface, semantic search, faceted search, data visualization, etc.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Ontotext

AUGUST 16, 2019

The answers to these questions are presented in the course of week-long, self-paced sessions and a 4.5-hour Another thing you should not expect from this training is presenting use cases from different domains. hour live online practice session.

Knowledge Discovery 40

Knowledge Discovery Technology Metadata Interactive 40

Domino Data Lab

DECEMBER 4, 2020

We can also check for missing values, although it appears that none are present. 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. colwise(x -> any(ismissing.(x)),

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

Ontotext

APRIL 4, 2019

Some of this knowledge is locked and the company cannot access it. We translate their documents, presentations, tables, etc. into structured knowledge that can be processed by machines. We help our customers unlock it and make it usable so they can be more efficient. Smart Content Management and Recommendation Tools.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

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

FEBRUARY 21, 2024

Like many organizations, we want to get the most of the content we produce – technical documentation about our products, capabilities, past and current projects, research publications, marketing content, presentations, and webinars. 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

Domino Data Lab

AUGUST 1, 2021

Toy example to present intuition for LIME from Ribeiro (2016). Conference on Knowledge Discovery and Data Mining, pp. The black-box model’s complex decision function (unknown to LIME) is represented by the blue/pink background, which cannot be approximated well by a linear model. Ribeiro, M. Guestrin, C., Why should I trust you?:

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

The Unofficial Google Data Science Blog

JANUARY 14, 2016

Unlike experimentation in some other areas, LSOS experiments present a surprising challenge to statisticians — even though we operate in the realm of “big data”, the statistical uncertainty in our experiments can be substantial. Because individual observations have so little information, statistical significance remains important to assess.

Experimentation 42

Experimentation Statistics Metrics Measurement 42