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Enhancing Knowledge Discovery: Implementing Retrieval Augmented Generation with Ontotext Technologies

Ontotext

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.

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GraphDB in Action: Navigating Knowledge About Living Spaces, Cyber-physical Environments and Skies 

Ontotext

Buildings That Almost Think For Themselves About Their Occupants The first paper we are very excited to talk about is Knowledge Discovery Approach to Understand Occupant Experience in Cross-Domain Semantic Digital Twins by Alex Donkers, Bauke de Vries and Dujuan Yang.

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Are You Content with Your Organization’s Content Strategy?

Rocket-Powered Data Science

Do you present your employees with a present for their innovative ideas? If you include the title of this blog, you were just presented with 13 examples of heteronyms in the preceding paragraphs. Do you converse with your employees about decisions that might be the converse of what they would expect? Can you find them all?

Strategy 267
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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

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. This, of course, has its challenges and turning points, but Atanas provided solid advice for those wondering where to start at the end of his presentation.

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At Center Stage: 2 Ontotext Webinars About Reasoning with Big Knowledge Graphs and the Power of Cognitive Graph Analytics

Ontotext

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.

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Unlocking the Power of Better Data Science Workflows

Smart Data Collective

With the data analyzed and stored in spreadsheets, it’s time to visualize the data so that it can be presented in an effective and persuasive manner. Phase 4: Knowledge Discovery. This is also the period where specific questions are asked and confusion is cleared up. Phase 3: Data Visualization.

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Business Intelligence System: Definition, Application & Practice

FineReport

In general, business intelligence (BI) system consists of three main parts: complete collection of data, reasonable arrangement and presentation of data, and delivery of data to those who need it in a convenient and efficient manner. It is an active method of automatic discovery. Data Visualization.