Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. SIGKDD is ACM’s Special Interest Group on Knowledge Discovery and Data Mining.?The 1989 to be exact. The details are below.

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KDD Knowledge Discovery Data mining Statistics 81

Ontotext

DECEMBER 1, 2023

Lance Paine, Director and Principal Semantic Consultant at Semantic Partners presenting at KGF 2023 These ideas were further addressed at the panel “How can organizations streamline and speed up knowledge graph implementation of enterprise semantic applications?”.

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Metadata Sales Consulting Enterprise 78

Ontotext

SEPTEMBER 15, 2020

The use of knowledge graphs doesn’t try to enforce yet another format on the data but instead overlays a semantic data fabric, which virtualizes the data at a level of abstraction more closely to how the users want to make use of the data. It is also better interconnected, which brings more content and enables deeper analytics.

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Metadata Knowledge Discovery Data Quality Strategy 69

Ontotext

OCTOBER 28, 2021

In the context of the FROCKG project, we have connected metaphactory to this knowledge graph created with and hosted in GraphDB. Let’s first have a look at the knowledge graph management capabilities provided by metaphactory. Visual Ontology Modeling With metaphactory.

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Visualization Interactive Knowledge Discovery Modeling 52

Ontotext

MAY 18, 2020

These are the so-called supercomputers, led by a smart legion of researchers and practitioners in the fields of data-driven knowledge discovery. Again, the overall aim is to extract knowledge from data and, through algorithms based on artificial intelligence, to assist medical professionals in routine diagnostics processes.

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Knowledge Discovery Experimentation Data-driven Metadata 72

The Unofficial Google Data Science Blog

JULY 22, 2020

For example, consider a smaller website that is considering adding a video hosting feature to increase engagement on the site. The fantasy football and video hosting examples, which we will discuss in more detail later, highlight situations where this design might be considered, despite potential complexity in the analysis.

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Experimentation Statistics Testing Strategy 95

Ontotext

FEBRUARY 21, 2024

The examples below use OpenAI’s ChatGPT, but they can be applied against other LLM chatbots, including self-hosted ones. The post Enhancing Knowledge Discovery: Implementing Retrieval Augmented Generation with Ontotext Technologies appeared first on Ontotext. Talk to Your Graph GraphDB 10.4

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Knowledge Discovery Technology Metadata Data-driven 64