Using the Graph Data Science library
In the previous module, you learned about unweighted shortest paths and the built-in Full definition for Cypher (opens in a new tab)Neo4j's implementation of GQL, the ISO standard query language for graph databases. It is declarative: you describe the pattern to find, and the database decides how to find it. functions that allow you to identify them.
This module will introduce the concept of weighted Full definition for relationship (opens in a new tab)A named, directed connection between two nodes. Every relationship has a type, a start node and an end node. and how to find shortest weighted paths with the Go to glossary for graph data science (opens in a new tab)Analysing data through the structure of its connections. Also the name of the Neo4j library that implements it. library.
In this module, you will learn:
- The characteristics of a weighted relationship.
- How to find shortest weighted paths using Full definition for Dijkstra's algorithm (opens in a new tab)An algorithm that finds the cheapest route between two nodes..
- How to find k-shortest weighted paths using Full definition for Yen's algorithm (opens in a new tab)An algorithm that finds the k cheapest routes between two nodes, rather than only the cheapest..