Question Answering based on Knowledge Graphs | LinkedIn
Why Question-Answering Engines? The search only for documents is outdated. Users who have already adopted a question-answering (QA) approach with their personal devices, e.
SpikeX - SpaCy Pipes for Knowledge Extraction • A collection of pipes ready to be plugged in a spaCy pipeline. It aims to help in building knowledge extraction...
We launched Stardog Free today, offering you the flexibility to explore Stardog for your project without commercial limitations. Check it out and enjoy...
The Pros and Cons of RDF-Star and Sparql-Star | LinkedIn
For regular readers of the (lately somewhat irregularly published) The Cagle Report, I've finally managed to get my feet underneath me at Data Science Central, and am gearing up with a number of new initiatives, including a video interview program that I'm getting underway as soon as I can get the l
SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization
SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization • A subgraph extraction module that can efficiently anchor ...
Helpful juxtaposition of various modelling paradigms. Thoughtprovoking, too, when you look at the column to the right. Even though things seem to be in... 16 comments on LinkedIn
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answeri
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering - The problem of answering questions using knowledge from pre-trained...
What if two of the hottest graph frameworks come together? You better come to the party! Leverages the flexibility of GraphQL in the frontend with the ... 16 comments on LinkedIn
Katana Graph Partners with Intel on 3rd Gen Intel Xeon Scalable Processors
AUSTIN, TX – April 06, 2021 – Katana Graph, a high performance scale-out graph processing, AI and analytics company, announced today that it has optimized its graph engine for the new 3rd Gen Intel Xeon Scalable processor and memory systems. Katana Graph can now take advantage of the latest generation Intel Xeon Scalable processors and […]
The future of search is the rise of intelligent data and documents.
Way back in 1991, Tim Berners-Lee, then a young English software developer working at CERN…
Ontologies, NLP, Semantic Interoperability... it's all graphs | LinkedIn
Is it me or the Twitter graph and the LinkedIn graph feel a bit disconnected? I personally tend to interact more with the first and that's why I have the impression that the second might be missing out on some of the nice and "graphy" content that I've been producing lately. This article is just a c
Linked Data is a universal approach for naming, shaping, and giving meaning to data, using open standards. It was meant to be the second big information
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Relational databases schemes are essentially driven by normalization, not by real-world relationships. One of my longest SQL query has beaten 4000 lines... 12 comments on LinkedIn
I worked on some experiments on RDF-to-text generation. The goal is to generate coherent multi-sentence texts from data in a knowledge graph. While not...
Supercharge your knowledge graph using Amazon Neptune, Amazon Comprehend, and Amazon Lex | Amazon Web Services
Knowledge graph applications are one of the most popular graph use cases being built on Amazon Neptune today. Knowledge graphs consolidate and integrate an organization’s information into a single location by relating data stored from structured systems (e.g., e-commerce, sales records, CRM systems) and unstructured systems (e.g., text documents, email, news articles) together in a […]