Graph Algorithms Supported In Neo4j

Kevin Feasel

2018-04-30

Graph

Amy Hodler gives us a quick summary of fifteen separate algorithms for traversing a graph in Neo4j:

6. PageRank

What it does: Estimates a current node’s importance from its linked neighbors and then again from their neighbors. A node’s rank is derived from the number and quality of its transitive links to estimate influence. Although popularized by Google, it’s widely recognized as a way of detecting influential nodes in any network.

How it’s used: PageRank is used in quite a few ways to estimate importance and influence. It’s used to suggest Twitter accounts to follow and for general sentiment analysis.

PageRank is also used in machine learning to identify the most influential features for extraction. In biology, it’s been used to identify which species extinctions within a food web would lead to biggest chain reaction of species death.

If you are interested in getting into graph databases, it’s useful to know these algorithms.

Related Posts

Traversing Nearest Neighbors With Dijkstra’s Algorithm And SQL Server Graph

James Livingston gives us a Powershell-based implementation of Dijkstra’s shortest path algorithm: In my previous post I shared a SQL Server 2017 graph database of US capitals. Graphs are a computer science core competency and present some interesting challenges for programmers. Most notable of these challenges is finding the shortest path between nodes. Dijkstra’s algorithm is a commonly […]

Read More

A Graph Database Of US Capitals

Kevin Feasel

2018-12-11

Graph

James Livingston has a graph database to share: While there’s countless relational databases out there for practice, there’s not much in the way of graph databases. It is my intent to share my graph databases with the world in hopes that it removes the friction associated with your learning.US Capitals is a popular data set […]

Read More

Categories

April 2018
MTWTFSS
« Mar May »
 1
2345678
9101112131415
16171819202122
23242526272829
30