Building a Meetup Recommendation Engine with Spring Data Neo4j

Explore the process of building a meetup recommendation engine using Spring Data Neo4j in this 51-minute conference talk from Spring I/O 2016. Dive into the world of graph databases and learn how to leverage Meetup.com's data APIs to create a powerful recommendation system. Discover the advantages of using a property graph model over traditional relational databases for this type of application. Follow along as the speaker demonstrates how to implement the recommendation engine using Spring Boot and Spring Data Neo4j, covering topics such as domain modeling, data import strategies, and REST controller implementation. Gain insights into finding similar meetup groups, understanding what makes groups similar, and writing efficient Cypher queries for pattern matching in Neo4j. By the end of this talk, acquire the knowledge to create your own recommendation engine using web APIs or other data sources, applicable to various domains beyond meetups.

Intro
And Today's Requirements
The Whiteboard Model is the Physical Model
Property Graph Model
Relational to Graph Relational
Neo4 : All About Patterns
Quick History of SD-Neo4j
Quick History of SDN
Spring Data Neo4j 4. Features
Entities in Domain
Meetup Domain Model
What makes groups similar?
Find similar groups to Neo4j
Graph Pattern in Cypher
Find my similar groups
Data: Meetup API & Spring Social
Code: Meetup API & Spring Social
Data Import Alternative
Configuration: Spring Boot
Entities: Group
Entities: Event
Entities: Rating
Repositories - Topic
REST Controllers
SDN4.1: Resources