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Neo4j Graph Data Science
Although Neo4j has traditionally been used for transaction workloads, in recent years it is increasingly being used at the heart of graph analytics platforms. This guide introduces the tools available for applying graph analytics to your connected data.
The Neo4j Graph Data Science Library (GDSL) provides efficiently implemented, parallel versions of common graph algorithms for Neo4j 3.x and Neo4j 4.x exposed as Cypher procedures.
The library contains implementations of classic graph algorithms in the path finding, centrality, and community detection categories. It also includes algorithms that are well suited for data science problems, like link prediction and weighted and unweighted similarity.
NEuler (Neo4j Euler) is a graph app that helps Neo4j Desktop users get started with the Neo4j Graph Data Science Library.
Neo4j offers powerful querying capabilities for structured data, but a lot of the world’s data exists in text documents. NLP techniques can help to extract the latent structure in these documents.
In O’Reilly’s Graph Algorithms Book, Amy Hodler and Mark Needham take you on a guided tour of the world of graph algorithms.
The book contains detailed sections on each algorithm, explaining both why and how to use them, along with examples based on the Neo4j Graph Data Science Library and Apache Spark GraphFrames.