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Milo Graph - HACKATHON
The document discusses a hackathon held to develop a recommendation system using graph databases and microservices. The team created relationships between vertices like products and users to generate recommendations based on similarity. They built the system using MongoDB, MySQL, and other technologies. It was then deployed on a client's website to test in a real-world environment. Next steps include scaling the system and analyzing the graph data.
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Milo Graph - HACKATHON
- 1. Milo graph Leonardo Berdu JoséGuilherme Tavares leonardo.berdu@stored.com.br guilherme.tavares@stored.com.br HACKATHON
- 2. Milo graph WHY? • becreative to generate ideas • good way to learn fast and learn new technologies, in this case: micro-services, mongoDB, graphs • team integration • develop our own recommendation system • agile manifesto • M.V.P in one weekend
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- 4. Milo graph HACKATHON -3rd DAY
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- 6. Milo graph GRAPH RECOMMENDATION •create relationships between two vertices (product, person, office, etc) • learn machine x time • edges with higher coefficient defines the best relevance between vertices • clustering tendency
- 7. Milo graph GRAPH RECOMMENDATION •vertices (eg. products) • edges (relevance between vertices — eg. number of visits)
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- 9. Milo graph MONGODB • sharding •high performance • open source • NoSQL https://www.mongodb.org/
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- 13. Milo graph MILO POST POSTAPI data validation celery • fast processing in API • async • mongoDB and mySQL writing
- 14. Milo graph MILO GET GETAPI mongoDB response • performance
- 15. Milo graph MILO REALGRAPH running in a real client www.gsnsuplementos.com.br
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- 18. Milo graph TEAM Rafael Bouchabki GuilhermeTavares Michael Coelho Fernando Chimicoviaki Leonardo Berdu Hebert Silva back-end front-end
- 19. Milo graph NEXT STEPS •scale to big data • update to a big data database • graph analisys • launch as a product (monetization)
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