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Ontotext Marketing Gets a Boost from Knowledge Graph Powered LLMs

Ontotext

We envisioned harnessing the power of our products to elevate our entire content publishing process, thereby facilitating in-depth knowledge exploration. OTKG models information about Ontotext, combined with content produced by different teams inside the organization. What is OTKG?

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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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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

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GraphDB and metaphactory Part II: An RDF Database and A Knowledge Graph Platform in Action

Ontotext

However, although some ontologies or domain models are available in RDF/OWL, many of the original datasets that we have integrated into Ontotext’s Life Sciences and Healthcare Data Inventory are not. Visual Ontology Modeling With metaphactory. This makes it much easier to collaborate and discuss specific parts of the model.

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AI, the Power of Knowledge and the Future Ahead: An Interview with Head of Ontotext’s R&I Milena Yankova

Ontotext

Milena Yankova : We help the BBC and the Financial Times to model the knowledge available in various documents so they can manage it. Milena Yankova : What we did for the BBC in the previous Olympics was that we helped journalists publish their reports faster. What exactly do you do for them? I think artists can relax.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

Companies like Google [2], Amazon [3], and Microsoft [4] have all published scholarly articles on this topic. In practice, one may want to use more complex models to make these estimates. For example, one may want to use a model that can pool the epoch estimates with each other via hierarchical modeling (a.k.a.

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The Semantic Web: 20 Years And a Handful of Enterprise Knowledge Graphs Later

Ontotext

One of its pillars are ontologies that represent explicit formal conceptual models, used to describe semantically both unstructured content and databases. The second one is the Linked Open Data (LOD): a cloud of interlinked structured datasets published without centralized control across thousands of servers.