Discover what's new in the 3.5 release of the Neo4j graph database, including a Go language driver, full-text search and indexing, TLS encryption and more.

based Gruff Drives Infinite Data Integration, Holistic Insights and Complex Reasoning

“Q: which product taxonomies are used in the Shopping / Ad industries? Google's Product Taxonomy is a de facto standard but it lacks freshness, coverage and/or finesse in some areas. I'm also looking at product taxonomies from Amazon, Ebay, Walmart, Target, Groupon. What else?”

Graphs are common #data structures to represent #connecteddata. To use graphs with #deeplearning, we use graph embeddings, a low dimension representations which helps generalize input data. Node2Vec aims to preserve network neighborhoods #datascience #AI

https://douroucouli.wordpress.com/2019/05/10/obographviz-0-2-2-released-now-with-visualization-of-equivalence-cliques/

Eerily good timing, this is the perfect dataset for item 2: https://t.co/gBhtIylbvJ https://t.co/vOf3jEX7F7— Octavian.ai (@Octavian_ai) April 3, 2019

Keynote talk given at the 41st European Conference on Information Retrieval (ECIR 2019)

In this review, we provide a summary of recent progress in ontology mapping (OM) at a crucial time when biomedical research is under a deluge of an in…

Technology research and analyst house Bloor Research places Ontotext as champion among RDF graph providers in its latest update on the graph database market

The scope of fraud management for financial crimes has reached global proportions. Financial service organizations are contending with measures for Anti-Money

Updates on #knowledgegraphs affect services built on top of them. But not all changes are the same: some updates drastically change the result of operations based on knowledge graph content; others do not lead to any variation #research #award #iswc_conf

In this paper, an overview of the state of the art on knowledge graph

An #opensource #software framework to build Games with Purpose for #linkeddata refinement: Web applications to crowdsource partial ground truth, by motivating user participation through fun incentives #knowledgegraph #datascience #data #opendata #research

Learn advanced Cypher queries for one approach to analyzing data inconsistencies directly in your flexible and forgiving Neo4j graph database.

Learn why semantic technology is not only about technology, but also about the way an enterprise sees the world and its place in the digital landscape.

Incident response involving human responders requires context of systems and services that are encountering issues. Getting this context…

learning by itself is only half a solution.To explain this (and the relationship that graphs have to machine learning and AI), it's worth spending a bit of time exploring what exactly machine learning does, how it works. Machine learning isn't actually one particular algorithm or piece of software, but rather the use of statistical algorithms to analyze large amounts of data and from that construct a model that can, at a minimum, classify the data consistently. If it's done right, the reasoning goes, it should then be possible to use that model to classify new information so that it's consistent with what's already known.Many such system

WHAT THIS TALK IS ABOUT My personal take on the history of human label collection ter to you

I realized that I needed to know what the constituent parts of data models really are. Across the board, all platforms, all models etc. Is there anything similar to atoms and the (chemical) bonds that enables the formation of molecules?

Boettiger, (2019). Ecological Metadata as Linked Data. Journal of Open Source Software, 4(34), 1276, https://doi.org/10.21105/joss.01276

For a domain with a strong focus on unambiguous identifiers and meaning, the Semantic Web research field itself has a surprisingly ill-defined sense of identity. Started at the end of the 1990s at the intersection of databases, logic, and Web, and influenced along the way by all major tech hypes such as Big Data and machine learning, our research community needs to look in the mirror to understand who we really are…

Two philosophers are using machine learning and artificial intelligence to create a real-time map of the global economy, and the world’s largest financial firms are lining up at its door.

.@TigerGraph #graphDB updates its #Cloud offering with configuration for distributed graphs, replica instances for high availability, EFS for backup/restore. Updates available by end of 2019 on #AWS, #Azure to follow in Q1 2020

“3.4.0 Highlights - The Gremlin Recipes have been expanded with a new Anti-Patterns section that describes common pitfalls around Gremlin readability, maintainability and performance. https://t.co/NwUNY7zFqY #graphdb”

Your one-stop introduction to the world of graph tech.

#ISWC2019 Reproducibility Initiative aims to enable easy sharing of code &experimentation setups, make more code & data available, highlight impact & increase credibility of #SemanticWeb #research, facilitate dissemination @michaelcochez @FrankVanHarmele

Graphs are a general-purpose #datamodel, as relational was a general-purpose #data model a generation ago. A supply chain is a graph. Knowledge is a graph. Graphs are very applicable in a wide range of use cases @jimwebber @TheRegister #GraphDB #tech [LINK]https://www.theregister.co.uk/2020/02/05/graph_database_neo4j_chief_scientist/ [LINK]https://regmedia.co.uk/2016/04/26/graph_database.jpg

Don’t ask what #GraphQL can do for the #SemanticWeb; ask what the SW can do for GraphQL, says @szymonklarman Perspective dominating analyses so far has been considering GraphQL an interface for #linkeddata. That's valid, but there's another way #research

Big data, semantic searches, and real-time responses are the reason behind the growing demand for graph databases. This article talks about what a graph database is, why graph databases are popular, and why and when we should use a graph database.