Discover what's new in the Neo4j community for the week of 20 January 2018, including projects around Kotlin, Categorical PageRank, and Dynamic Rule Based Decision Trees.
4. Thomas Frisendal has another installment of his series on
Knowledge Graphs. In this post Thomas wonders why
knowledge graphs are getting so much attention and
describes an architecture for the finance
industry with a knowledge graph at its
heart.
Knowledge graphs: Why?
dataversity.net/not-get-lost-2018-map-graph-go/
5. Neo4j Categorical Pagerank
Tomaz Bratanic wrote a post showing how to apply Kenny
Bastani's categorical PageRank to a Game of Thrones
dataset using Neo4j graph algorithms.
tbgraph.wordpress.com/2018/01/14/neo4j-categorical-pagerank/
6. On the podcast: Jesús Barrasa
This week on the podcast Rik interviews my colleague Jesús
Barrasa about his new job leading the telecoms practice at
Neo4j. Jesus explains the common use cases he sees for
graphs in the telecom space such as dependency
modelling and root cause analysis and his hopes
that graphs will become ubiquitous in this space.
blog.bruggen.com/2018/01/podcast-interview-with-jesus-barrasa.html
7. Dynamic Rule Based Decision Trees using Neo4j.
maxdemarzi.com/2018/01/14/dynamic-rule-based-decision-trees-in-neo4j/
Max De Marzi wrote a blog post in which he showed how
to build a dynamic rule based decision trees using Neo4j. In
the post Max explains how to write a procedure that
explores rules using the Neo4j Traversal API and evaluates
predicate expressions using the
Janino Java compiler.
8. How Graphs Changed The Way Hackers Attack
At GraphConnect NYC 2017 Andy Robbins talked about
BloodHound, a tool he created that uses graph theory to
show how attackers breach and
take over modern corporate
network.
youtube.com/watch?v=cT4xEhssz0U
9. If you liked this check out the blog post
neo4j.com/blog/this-week-neo4j-kotlin-dynamic-decision-trees-categorical-pagerank/