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Andrei Kashcha on Twitter
Andrei Kashcha on Twitter
https://t.co/7T0EOs6yG7 - Made this tiny tool to discover related subreddits.The graph is created based on jaccard similarity between two subreddits. Jaccard similarity is constructed from set of shared users.Source code https://t.co/J9r1jl1JjR pic.twitter.com/4hcg7mI4sg— Andrei Kashcha (@anvaka) January 10, 2019
·twitter.com·
Andrei Kashcha on Twitter
Announcing Neo4j for Graph Data Science
Announcing Neo4j for Graph Data Science
grade features and scale. We appreciate your candid stories and collaboration, and we’ve used this to create a better solution. As such, we’re excited to announce Neo4j for Graph Data Science™, the first data science environment built to harness the predictive power of relationships for enterprise deployments. Neo4j for Graph Data Science is an ecosystem of tools that includes: With Neo4j for Graph Data Science, data scientists are empowered to confide
·neo4j.com·
Announcing Neo4j for Graph Data Science
CS 520: Knowledge Graphs
CS 520: Knowledge Graphs
Knowledge graphs have emerged as a compelling abstraction for organizing world's structured knowledge over the internet, capturing relationships among key entities of interest to enterprises, and a way to integrate information extracted from multiple data sources. Knowledge graphs have also started to play a central role in machine learning and natural language processing as a method to incorporate world knowledge, as a target knowledge representation for extracted knowledge, and for explaining what is being learned. This class is a graduate level research seminar featuring prominent researchers and industry practitioners working on different aspects of knowledge graphs. It will showcase how latest research in AI, database systems and HCI is coming together in integrated intelligent systems centered around knowledge graphs.The seminar will be offered over Zoom as per the planned schedule.The seminar is open to public. Remote participants may join the seminar through Zoom. To be
·web.stanford.edu·
CS 520: Knowledge Graphs
Do Graph Databases Scale? - DZone Big Data
Do Graph Databases Scale? - DZone Big Data
Graph Databases are a great solution for many modern use cases: Fraud Detection, Knowledge Graphs, Asset Management, Recommendation Engines, IoT, Permission Management … you name it.  All such projects benefit from a database technology capable of analyzing highly connected data points and their relations fast – Graph databases are designed for these tasks. But the nature of graph data poses challenges when it comes to *buzzword alert* scalability. So why is this, and are graph databases capable of scaling? Let’s see... In the following, we will define what we mean by scaling, take a closer look at two challenges potentially hindering scaling with graph databases, and discuss solutions currently available. What Is the “Scalability of Graph Databases”? Let’s quickly define what we mean here by scaling, as it is not “just” putting more data on one machine or throwing it on various ones. What you want when working with large or growing datasets is also an acceptabl
·dzone.com·
Do Graph Databases Scale? - DZone Big Data
Extracting Synonyms from Knowledge Graphs
Extracting Synonyms from Knowledge Graphs
based search systems do not reflect the semantics of individual input words of search queries. For example, a query for the word “house” would not return records for the words “building” or “real estate”. How can such relationships be represented in a technical system? One approach is to include synonyms. Search engines like Elasticsearch provide methods to integrate synonym lists. However, a list of synonyms itself is required for configuration.
·dice-research.org·
Extracting Synonyms from Knowledge Graphs
Global Graph Database Market Size, Prospects, Growth Trends, Key Trend, Future Expectations and Forecast from 2019 to 2025 – Express Press Release Distribution
Global Graph Database Market Size, Prospects, Growth Trends, Key Trend, Future Expectations and Forecast from 2019 to 2025 – Express Press Release Distribution
Albany, US, 2019-Jan-23 — /EPR Network/ —Market Research Hub (MRH) has actively included a new research study titled “Global Graph Database Market” Size
·express-press-release.net·
Global Graph Database Market Size, Prospects, Growth Trends, Key Trend, Future Expectations and Forecast from 2019 to 2025 – Express Press Release Distribution
Graph data modelling - inferred vs explicit categories and labels – pablissimo.com
Graph data modelling - inferred vs explicit categories and labels – pablissimo.com
When building graph data models we frequently have to deal with a degree of polymorphism for our entities just like the real world. For instance – I’m a person, but I’m also a parent, a spouse, a sibling, a child, a… Implicit categorisation Sometimes the entity categories are entirely defined by relationships to other entities. […]
·pablissimo.com·
Graph data modelling - inferred vs explicit categories and labels – pablissimo.com