**Table of Contents**

- 7.1. User roles in graphs
- 7.2. ACL structures in graphs
- 7.3. Linked Lists
- 7.4. Hyperedges
- 7.5. Basic friend finding based on social neighborhood
- 7.6. Co-favorited places
- 7.7. Find people based on similar favorites
- 7.8. Find people based on mutual friends and groups
- 7.9. Find friends based on similar tagging
- 7.10. Multirelational (social) graphs
- 7.11. Implementing newsfeeds in a graph
- 7.12. Boosting recommendation results
- 7.13. Calculating the clustering coefficient of a network
- 7.14. Pretty graphs
- 7.15. A multilevel indexing structure (path tree)
- 7.16. Complex similarity computations
- 7.17. The Graphity activity stream model

The following chapters contain simplified examples of how different domains can be modeled using Neo4j. The aim is not to give full examples, but to suggest possible ways to think using nodes, relationships, graph patterns and data locality in traversals.

The examples use Cypher queries a lot, read Part III, “Cypher Query Language” for more information.

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