article thumbnail

Enhancing Knowledge Discovery: Implementing Retrieval Augmented Generation with Ontotext Technologies

Ontotext

RAG and Ontotext offerings: a perfect synergy RAG is an approach for enhancing an existing large language model (LLM) with external information provided as part of the input prompt, or grounding context. So we have built a dataset using schema.org to model and structure this content into a knowledge graph.

article thumbnail

KDD 2020 Opens Call for Papers

Data Science 101

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.

KDD 81
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

On the Hunt for Patterns: from Hippocrates to Supercomputers

Ontotext

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.

article thumbnail

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

Ontotext

Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises. from Q&A with Tim Berners-Lee ) Finally, Sumit highlighted the importance of knowledge graphs to advance semantic data architecture models that allow unified data access and empower flexible data integration.

article thumbnail

From Data Silos to Data Fabric with Knowledge Graphs

Ontotext

There must be a representation of the low-level technical and operational metadata as well as the ‘real world’ metadata of the business model or ontologies. The multiple and varying ‘views’ of the data are now possible without modifying the data at its source or the host system. Integrate data with ETL or virtualization.

article thumbnail

Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

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.

article thumbnail

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.