Hands-on graph analytics with Neo4j /

Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learning Key Features Get up and running with graph analytics with the help of real-world examples Explore various use cases such as fraud detection, graph-...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Scifo, Estelle (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham, UK : Packt Publishing, [2020]
Temas:
Graph databases.
Graph databases
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright and Credits
  • About Packt
  • Contributors
  • Table of Contents
  • Preface
  • Section 1: Graph Modeling with Neo4j
  • Chapter 1: Graph Databases
  • Graph definition and examples
  • Graph theory
  • A bit of history: the Seven Bridges of Königsberg problem
  • Graph definition
  • Visualization
  • Examples of graphs
  • Networks
  • Road networks
  • Computer networks
  • Social networks
  • Your data is also a graph
  • Moving from SQL to graph databases
  • Database models
  • SQL and joins
  • It's all about relationships
  • Neo4j
  • the nodes, relationships, and properties model
  • Building blocks
  • Nodes
  • Relationships
  • Properties
  • SQL to Neo4j translator
  • Neo4j use cases
  • Understanding graph properties
  • Directed versus undirected
  • Weighted versus unweighted
  • Cyclic versus acyclic
  • Dense versus sparse
  • Graph traversal
  • Connected versus disconnected
  • Considerations for graph modeling in Neo4j
  • Relationship orientation
  • Node or property?
  • Summary
  • Further reading
  • Chapter 2: The Cypher Query Language
  • Technical requirements
  • Creating nodes and relationships
  • Managing databases with Neo4j Desktop
  • Creating a node
  • Selecting nodes
  • Filtering
  • Returning properties
  • Creating a relationship
  • Selecting relationships
  • The MERGE keyword
  • Updating and deleting nodes and relationships
  • Updating objects
  • Updating an existing property or creating a new one
  • Updating all properties of the node
  • Updating node labels
  • Deleting a node property
  • Deleting objects
  • Pattern matching and data retrieval
  • Pattern matching
  • Test data
  • Graph traversal
  • Orientation
  • The number of hops
  • Variable-length patterns
  • Optional matches
  • Using aggregation functions
  • Count, sum, and average
  • Creating a list of objects
  • Unnesting objects
  • Importing data from CSV or JSON
  • Data import from Cypher
  • File location
  • Local file: the import folder
  • Changing the default configuration to import a file from another directory
  • CSV files
  • CSV files without headers
  • CSV files with headers
  • Eager operations
  • Data import from the command line
  • APOC utilities for imports
  • CSV files
  • JSON files
  • Importing data from a web API
  • Setting parameters
  • Calling the GitHub web API
  • Summary of import methods
  • Measuring performance and tuning your query for speed
  • Cypher query planner
  • Neo4j indexing
  • Back to LOAD CSV
  • The friend-of-friend example
  • Summary
  • Questions
  • Further reading
  • Chapter 3: Empowering Your Business with Pure Cypher
  • Technical requirements
  • Knowledge graphs
  • Attempting a definition of knowledge graphs
  • Building a knowledge graph from structured data
  • Building a knowledge graph from unstructured data using NLP
  • NLP
  • Neo4j tools for NLP
  • GraphAware NLP library
  • Importing test data from the GitHub API
  • Enriching the graph with NLP

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