GraphNews

How to calculate TF-IDF in @Neo4j using only Cypher. TD-IDF is used in an #NLP pipeline to calculate the importance of a term within a document compared to a set of documents as a whole.Say you have a model of (:Document)-[:MENTIONS]->(:Term)1/— Adam Cowley (@adamcowley) April 6, 2019

#AI startup Adarga closed a £5M Series A #funding. Adarga allows organizations to transform normally data-intensive, human knowledge processes by analyzing vast volumes of #data. Adarga clients can build up a #KnowledgeGraph about subjects and targets

I would like to point to a crowd-funding of 📊 @rawgraphs, a project I find super interesting for a while and now they want to rewrite it. I think SPARQL and RAWGraphs can become best friends and so do they so help them getting there! https://t.co/VI0gK0ZZIS pic.twitter.com/UszINmFyuw— Adrian Gschwend (@linkedktk) October 2, 2019

“My interpretation of the W3C Graph Workshop wrap-up session today in Berlin. Sorry for the ones I left out, I focus on the ones I participated/understood, mostly around RDF. Feel free to contribute! Sessions/minutes are linked here: https://t.co/P3oV4Xshwr #W3CGraphWorkshop 👇”

Swiss EPFL's Blue Brain Nexus Project @bluebrainnexus released Nexus v1.0, which is from what I can see among others a SPARQL endpoint. I did not play with it yet but sounds like something to check out! https://t.co/y30L5thM44— Adrian Gschwend (@linkedktk) April 3, 2019

How to query #Wikidata (or any other #LinkedData endppoint) from within #rstats? @kala_karu explains. Documented code here: https://t.co/L9b8CEJWNu #tutorial #datascience #knowledgegraph #data #tech h/t @linkedktk @statistik_zh

consuming because experts are required to pick out biomedical inte

Tamara Louie | Data Scientist, Discovery

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The Ontologies Community of Practice is engaged in the development of ontologies for agricultural research. In a series of blog posts, we’ll take a look at ongoing ontologies projects and developments.

Recent advances in high-throughput technologies have resulted in a tremendous increase in the amount of omics data produced in plant science. This increase, in conjunction with the heterogeneity and variability of the data, presents a major challenge to adopt an integrative research approach. We are facing an urgent need to effectively integrate and assimilate complementary datasets to understand the biological system as a whole. The Semantic Web offers technologies for the integration of heterogeneous data and their transformation into explicit knowledge thanks to ontologies. We have devel...

#Knowledgegraphs are a natural fit for knowledge management: they model domains to retain more context & meaning even as information is parsed and abstracted for digital representation. Information is modeled in a way that is more intuitive & useful

Read the fifth and final installment of our blog series on artificial intelligence and the ways AI explainability adds context for credibility.

Read the first installment of this blog series on artificial intelligence on the ways graph technology adds necessary context for powerful AI solutions.

Karuna Pande Joshi, University of Maryland, Baltimore County You’re trailing bits of personal data – such as credit card numbers,

Deep learning is transforming the field of artificial intelligence, yet it is lacking solid theoretical underpinnings. This state of affair significantly hinders further progress, as exemplified by time-consuming hyperparameters optimization, or the extraordinary difficulties encountered in adversarial machine learning. Our three-day workshop stems on what we identify as the current main bottleneck: understanding the geometrical […]

Causal reasoning is a necessary ingredient to human-level artificial intelligence. We're not there, yet.

Knowledge Representation is a key focus for most modern AI texts. Many AI experts feel that over half of their work is understanding how to find the right know…

The current artificial intelligence image recognition tools used in DAM systems are comparable to a pair of eyes disconnected from the brain.

Read about LinkedDataHub, how it developed as a Knowledge Graph management system and what you can use it for

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Alan Morrison's answer: Graph databases are often used to store knowledge graph data and the accompanying description, predicate and rule-based logic. Knowledge graph: A knowledge graph is a knowledge base that’s made machine readable with the help of logically consistent, linked graphs that tog...

What are your options for visualizing a network with many attributes? We review the alternatives and introduce a typology in a new state of the art report. #eurovis #datavis https://t.co/96dhomPTRt w. @carolinanobre84 @miriah_meyer @marc_streit 1/8 pic.twitter.com/PCAk5ptBp3— Alexander Lex (@alexander_lex) June 4, 2019

#knowledgegraph-based #research to design a 20 questions game on Bollywood movies. Uses probabilistic learning model for template-based question generation & answer prediction. Dataset of interrelated entities represented as weighted knowledge graph #AI