GMDSS - Practice1

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Christophe Willemsen

O BJE C TIF S :

VOTRE POSITION : 42*21'55N – 10*55'7E

VOUS VENEZ DE HEURTER UN ROCHER

A L'AIDE DES MOYENS DE DETRESSE A VOTRE
DISPOSITION, ENVOYEZ UN
MESSAGE DE DETRESSE :

1. UN MESSAGE LE PLUS RAPIDEMENT POSSIBLE

2. UN MESSAGE MUNI D'INFORMATIONS DESTINE A L
STATION COTIERE LA PLUS PROCHE

S IN O N ....

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Knowledge graphs + Chatbots with Neo4j

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The age of touch could soon come to an end. From smartphones and smartwatches, to home devices, in-car systems, touch is no longer the primary user interface. (source: Design News) During this talk, Christophe, Principal Consultant at GraphAware will walk you through the design of building Conversational Bots. To this end, he used Amazon Alexa and combined it with a Natural Language Processing stack backed by a Neo4j Graph Database. You will discover the basics of an Amazon Alexa skill and how the user experience with voice devices can be enhanced with graph based algorithms such as recommendations.

Chatbots and Voice Conversational Interfaces with Amazon Alexa, Neo4j and Gra...

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Graph Databases are naturally well-suited for building recommendation engines. In this talk, Christophe will share his experience building a number of production-ready recommendation engines using Neo4j and introduce the open-source GraphAware Reco4PHP Library, which enables PHP developers to rapidly build their own recommender systems. This presentation starts by a brief explanation of why graphs are a suitable data model for building recommender systems. A summary of typical recommendation engine requirements follows, including the business and technical challenges these requirements introduce. Afterwards, the talk dives into possible solutions of these challenges, both from business and architectural/design perspectives, and introduces the GraphAware Reco4PHP Library. What follows is a demonstration of how this open-source recommendation engine skeleton solves many of the issues and how it handles the "plumbing", so that developers can focus on expressing the business logic specific to their domain. A majority of examples in this talk are drawn from real-world use cases and the speaker's personal experience building recommendation engines. Attendees should have a very basic understanding of graph theory. Prior experience with Neo4j and the Cypher query language is a plus, but not necessary. Attendees will learn: * what is a recommendation engine and what it is good for * why graphs are a good fit for building one * what business and technical challenges one faces building a recommender * what possible solutions there are for these challenges * how to build a high-performance graph-based recommendation engine in minutes * real-world case studies

Your own recommendation engine with neo4j and reco4php - DPC16

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Graph Databases are naturally well-suited for building recommendation engines. In this talk, Christophe will share his experience building a number of production-ready recommendation engines using Neo4j and introduce the open-source GraphAware Reco4PHP Library, which enables PHP developers to rapidly build their own recommendation systems. This presentation starts by a brief explanation of why graphs are a suitable data model for building recommendation systems. A summary of typical recommendation engine requirements follows, including the business and technical challenges these requirements introduce. What follows is a demonstration of how this open-source recommendation engine skeleton solves many of the issues and how it handles the "plumbing", so that developers can focus on expressing the business logic specific to their domain. We will then see how this can be used in a Micro Edition of Symfony in order to isolate your recommendation as a microservice. A majority of examples in this talk are drawn from real-world use cases and the speaker's personal experience building recommendation engines. Attendees should have a very basic understanding of graph theory. Prior experience with Neo4j and the Cypher query language is a plus, but not necessary.

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GMDSS - Practice1

1. EXERCICE PRATIQUE

4. O BJE C TIF S : VOTRE POSITION : 42*21'55N – 10*55'7E VOUS VENEZ DE HEURTER UN ROCHER A L'AIDE DES MOYENS DE DETRESSE A VOTRE DISPOSITION, ENVOYEZ UN MESSAGE DE DETRESSE : 1. UN MESSAGE LE PLUS RAPIDEMENT POSSIBLE 2. UN MESSAGE MUNI D'INFORMATIONS DESTINE A L STATION COTIERE LA PLUS PROCHE S IN O N ....

GMDSS - Practice1

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GMDSS - Practice1