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Knowledge Graphs and Supply Chains | LinkedIn
Knowledge Graphs and Supply Chains | LinkedIn
Copyright 2024 Kurt Cagle / The Cagle Report From one of my readers: Hi Kurt, have you written any article on how a knowledge graph differ from inventory built using graph. We are in constant struggle to differentiate knowledge graph from inventory apps? Questions like can inventory systems built us
·linkedin.com·
Knowledge Graphs and Supply Chains | LinkedIn
Common Elements of Data Quality in the Age of AI - DQLabs
Common Elements of Data Quality in the Age of AI - DQLabs
[vc_row][vc_column width=”1/2″ css=”.vc_custom_1724344160150{padding-right: 70px !important;}”][vc_column_text]In the era of AI, data quality has become a critical factor for successful implementations. A study by MIT Sloan Management Review found that 85% of executives believe AI will offer significant competitive advantages, yet only 39% have an AI strategy in place. This gap highlights the importance of foundational elements […]
·dqlabs.ai·
Common Elements of Data Quality in the Age of AI - DQLabs
We-KNOW RAG 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 to 𝗥𝗔𝗚 leverages a 𝗴𝗿𝗮𝗽𝗵-𝗯𝗮𝘀𝗲𝗱 method
We-KNOW RAG 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 to 𝗥𝗔𝗚 leverages a 𝗴𝗿𝗮𝗽𝗵-𝗯𝗮𝘀𝗲𝗱 method
Passing this along (because I think it shows how this field is evolving) but also to make a point. RAG is only half the story. Use RDF2Vec or a similar encoder…
𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 to 𝗥𝗔𝗚 leverages a 𝗴𝗿𝗮𝗽𝗵-𝗯𝗮𝘀𝗲𝗱 method
·linkedin.com·
We-KNOW RAG 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 to 𝗥𝗔𝗚 leverages a 𝗴𝗿𝗮𝗽𝗵-𝗯𝗮𝘀𝗲𝗱 method
What It Takes To Build a Great Graph
What It Takes To Build a Great Graph
Our world is composed of relationships. Who we know, how we interact, how we transact — graphs structure information in this way…
·towardsdatascience.com·
What It Takes To Build a Great Graph
Knowledge Graph Developer Experience
Knowledge Graph Developer Experience
Now that W3C RDF Star will put Semantic Graphs on-par with Labelled Property Graphs, it is time to address the final barrier, and that is the developer…
·linkedin.com·
Knowledge Graph Developer Experience
Overcoming 6 Graph RAG Hurdles
Overcoming 6 Graph RAG Hurdles
Recent advancements in LLMs have sparked excitement about their potential to organize and utilize Knowledge Graphs. Microsoft's GraphRAG is a good starting… | 10 comments on LinkedIn
·linkedin.com·
Overcoming 6 Graph RAG Hurdles
Data Product Vocabulary (DPROD)
Data Product Vocabulary (DPROD)
The Data Product (DPROD) specification is a profile of the Data Catalog (DCAT) Vocabulary, designed to describe Data Products. This document defines the schema and provides examples for its use.
The Data Product (DPROD) specification is a profile of the Data Catalog (DCAT) Vocabulary, designed to describe Data Products. This document defines the schema and provides examples for its use. DPROD extends DCAT to enable publishers to describe Data Products and data services in a decentralized way. By using a standard model and vocabulary, DPROD facilitates the consumption and aggregation of metadata from multiple Data Marketplaces. This approach increases the discoverability of products and services, supports decentralized data publishing, and enables federated search across multiple sites using a uniform query mechanism and structure. The namespace for DPROD terms is https://ekgf.github.io/dprod/# The suggested prefix for the DPROD namespace is dprod DPROD follows two basic principles: Decentralize Data Ownership: To make data integration more efficient, tasks should be shared among multiple teams. DCAT helps by offering a standard way to publish datasets in a decentralized manner. Harmonize Data Schemas: Using shared schemas helps unify different data formats. For instance, the DPROD specification provides a common set of rules for defining a Data Product. You can extend this schema as needed. The DPROD specification builds on DCAT by connecting DCAT Data Services to DPROD Data Products using Input and output ports. These ports are used to publish and consume data from a Data Product. DPROD treats ports as dcat data services, so the data exchanged can be described using DCAT's highly expressive metadata around distributions and datasets. This approach also allows you to create your own descriptions for the data you are sharing. You can use a special property called conformsTo from DCAT to link to your own set of rules or guidelines for your data. The DPROD specification has four main aims: To provide unambiguous and sharable semantics to answer the question: 'What is a data product?' Be simple for anyone to use, but expressive enough to power large data marketplaces Allow organisations to reuse their existing data catalogues and dataset infrastructure To share common semantics across different Data Products and promote harmonisation
·ekgf.github.io·
Data Product Vocabulary (DPROD)
Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune | Amazon Web Services
Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune | Amazon Web Services
Retrieval Augmented Generation (RAG) is an innovative approach that combines the power of large language models with external knowledge sources, enabling more accurate and informative generation of content. Using knowledge graphs as sources for RAG (GraphRAG) yields numerous advantages. These knowledge bases encapsulate a vast wealth of curated and interconnected information, enabling the generation of responses that are grounded in factual knowledge. In this post, we show you how to build GraphRAG applications using Amazon Bedrock and Amazon Neptune with LlamaIndex framework.
·aws.amazon.com·
Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune | Amazon Web Services
Medical Graph RAG
Medical Graph RAG
LLMs and Knowledge Graphs: A love story 💓 Researchers from University of Oxford recently released MedGraphRAG. At its core, MedGraphRAG is a framework…
·linkedin.com·
Medical Graph RAG