Graphs are brilliant. They're really well studied and have some amazing properties, especially for predictive analytics. But then there's AI: it's super-cool and also has some amazing abilities to guess the future given the past.
So, which are we meant to choose? I'd argue we should use both.
In this talk we'll see how graphs give us a framework for contextualizing the world around us. We'll explore how simple rules from graph theory can evolve our model to show how it might be in the future.
But that's not all, we'll also see how we can take our graphs and feed them into our ML pipelines for better scores than simple row-wise data using graph neural nets. And we'll see how to learn on graphs directly with graph convolutional networks.
Finally, we'll close the loop by asking our machine learning to tell us about other queries we should be running against the input graph to find patterns in data we don’t even know are valuable today.
Atelier - Architecture d’applications de Graphes - GraphSummit Paris
Atelier - Architecture d’applications de Graphes
Participez à cet atelier pratique animé par des experts de Neo4j qui vous guideront pour découvrir l’intelligence contextuelle. En utilisant un jeu de données réel, nous construirons étape par étape une solution de graphes ; de la construction du modèle de données de graphes à l’exécution de requêtes et à la visualisation des données. L’approche sera applicable à de multiples cas d’usages et industries.
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...
Romain CAMPOURCY – Architecte Solution, Sopra Steria
Patrick MEYER – Architecte IA Groupe, Sopra Steria
La Génération de Récupération Augmentée (RAG) permet la réponse à des questions d’utilisateur sur un domaine métier à l’aide de grands modèles de langage. Cette technique fonctionne correctement lorsque la documentation est simple mais trouve des limitations dès que les sources sont complexes. Au travers d’un projet que nous avons réalisé, nous vous présenterons l’approche GraphRAG, une nouvelle approche qui utilise une base Neo4j générée pour améliorer la compréhension des documents et la synthèse d’informations. Cette méthode surpasse l’approche RAG en fournissant des réponses plus holistiques et précises.
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...
Charles Gouwy, Business Product Leader, Adeo Services (Groupe Leroy Merlin)
Alors que leur Knowledge Graph est déjà intégré sur l’ensemble des expériences d’achat de leur plateforme e-commerce depuis plus de 3 ans, nous verrons quelles sont les nouvelles opportunités et challenges qui s’ouvrent encore à eux grâce à leur utilisation d’une base de donnée de graphes et l’émergence de l’IA.
GraphSummit Paris - The art of the possible with Graph Technology
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphAware - Transforming policing with graph-based intelligence analysis
Petr Matuska, Sales & Sales Engineering Lead, GraphAware
Western Australia Police Force’s adoption of Neo4j and the GraphAware Hume graph analytics platform marks a significant advancement in data-driven policing. Facing the challenges of growing volumes of valuable data scattered in disconnected silos, the organisation successfully implemented Neo4j database and Hume, consolidating data from various sources into a dynamic knowledge graph. The result was a connected view of intelligence, making it easier for analysts to solve crime faster. The partnership between Neo4j and GraphAware in this project demonstrates the transformative impact of graph technology on law enforcement’s ability to leverage growing volumes of valuable data to prevent crime and protect communities.
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product Updates
David Pond, Lead Product Manager, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
What is OCR Technology and How to Extract Text from Any Image for Free
Discover the fascinating world of Optical Character Recognition (OCR) technology with our comprehensive presentation. Learn how OCR converts various types of documents, such as scanned paper documents, PDFs, or images captured by a digital camera, into editable and searchable data. Dive into the history, modern applications, and future trends of OCR technology. Get step-by-step instructions on how to extract text from any image online for free using a simple tool, along with best practices for OCR image preparation. Ideal for professionals, students, and tech enthusiasts looking to harness the power of OCR.
This PowerPoint presentation provides a comprehensive overview of Enterprise Resource Planning (ERP) systems. It covers the fundamental concepts, benefits, and key functionalities of ERP software, illustrating how it integrates various business processes into a unified system. From finance and HR to supply chain and customer relationship management, ERP facilitates efficient data management and decision-making across organizations. Whether you're new to ERP or looking to deepen your understanding, this presentation offers valuable insights into leveraging ERP for business success.
A Comparative Analysis of Functional and Non-Functional Testing.pdf
A robust software testing strategy encompassing functional and non-functional testing is fundamental for development teams. These twin pillars are essential for ensuring the success of your applications. But why are they so critical?
Functional testing rigorously examines the application's processes against predefined requirements, ensuring they align seamlessly. Conversely, non-functional testing evaluates performance and reliability under load, enhancing the end-user experience.
Ansys Mechanical enables you to solve complex structural engineering problems and make better, faster design decisions. With the finite element analysis (FEA) solvers available in the suite, you can customize and automate solutions for your structural mechanics problems and parameterize them to analyze multiple design scenarios. Ansys Mechanical is a dynamic tool that has a complete range of analysis tools.
Break data silos with real-time connectivity using Confluent Cloud Connectors
Connectors integrate Apache Kafka® with external data systems, enabling you to move away from a brittle spaghetti architecture to one that is more streamlined, secure, and future-proof. However, if your team still spends multiple dev cycles building and managing connectors using just open source Kafka Connect, it’s time to consider a faster and cost-effective alternative.
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CViewSurvey Digitech Pvt Ltd that works on a proven C.A.A.G. model.
CViewSurvey is a SaaS-based Web & Mobile application that provides digital transformation to traditional paper surveys and feedback for customer & employee experience, field & market research that helps you evaluate your customer's as well as employee's loyalty.
With our unique C.A.A.G. Collect, Analysis, Act & Grow approach; business & industry’s can create customized surveys on web, publish on app to collect unlimited response & review AI backed real-time data analytics on mobile & tablets anytime, anywhere. Data collected when offline is securely stored in the device, which syncs to the cloud server when connected to any network.
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BT & Neo4j: Knowledge Graphs for Critical Enterprise Systems.pptx.pdfNeo4j
Presented at Gartner Data & Analytics, London Maty 2024. BT Group has used the Neo4j Graph Database to enable impressive digital transformation programs over the last 6 years. By re-imagining their operational support systems to adopt self-serve and data lead principles they have substantially reduced the number of applications and complexity of their operations. The result has been a substantial reduction in risk and costs while improving time to value, innovation, and process automation. Join this session to hear their story, the lessons they learned along the way and how their future innovation plans include the exploration of uses of EKG + Generative AI.
Atelier - Architecture d’applications de Graphes - GraphSummit ParisNeo4j
Atelier - Architecture d’applications de Graphes
Participez à cet atelier pratique animé par des experts de Neo4j qui vous guideront pour découvrir l’intelligence contextuelle. En utilisant un jeu de données réel, nous construirons étape par étape une solution de graphes ; de la construction du modèle de données de graphes à l’exécution de requêtes et à la visualisation des données. L’approche sera applicable à de multiples cas d’usages et industries.
Atelier - Innover avec l’IA Générative et les graphes de connaissancesNeo4j
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Allez au-delà du battage médiatique autour de l’IA et découvrez des techniques pratiques pour utiliser l’IA de manière responsable à travers les données de votre organisation. Explorez comment utiliser les graphes de connaissances pour augmenter la précision, la transparence et la capacité d’explication dans les systèmes d’IA générative. Vous partirez avec une expérience pratique combinant les relations entre les données et les LLM pour apporter du contexte spécifique à votre domaine et améliorer votre raisonnement.
Amenez votre ordinateur portable et nous vous guiderons sur la mise en place de votre propre pile d’IA générative, en vous fournissant des exemples pratiques et codés pour démarrer en quelques minutes.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j
Dr. Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Découvrez les dernières innovations de Neo4j, et notamment les dernières intégrations cloud et les améliorations produits qui font de Neo4j un choix essentiel pour les développeurs qui créent des applications avec des données interconnectées et de l’IA générative.
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...Neo4j
Romain CAMPOURCY – Architecte Solution, Sopra Steria
Patrick MEYER – Architecte IA Groupe, Sopra Steria
La Génération de Récupération Augmentée (RAG) permet la réponse à des questions d’utilisateur sur un domaine métier à l’aide de grands modèles de langage. Cette technique fonctionne correctement lorsque la documentation est simple mais trouve des limitations dès que les sources sont complexes. Au travers d’un projet que nous avons réalisé, nous vous présenterons l’approche GraphRAG, une nouvelle approche qui utilise une base Neo4j générée pour améliorer la compréhension des documents et la synthèse d’informations. Cette méthode surpasse l’approche RAG en fournissant des réponses plus holistiques et précises.
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...Neo4j
Charles Gouwy, Business Product Leader, Adeo Services (Groupe Leroy Merlin)
Alors que leur Knowledge Graph est déjà intégré sur l’ensemble des expériences d’achat de leur plateforme e-commerce depuis plus de 3 ans, nous verrons quelles sont les nouvelles opportunités et challenges qui s’ouvrent encore à eux grâce à leur utilisation d’une base de donnée de graphes et l’émergence de l’IA.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphAware - Transforming policing with graph-based intelligence analysisNeo4j
Petr Matuska, Sales & Sales Engineering Lead, GraphAware
Western Australia Police Force’s adoption of Neo4j and the GraphAware Hume graph analytics platform marks a significant advancement in data-driven policing. Facing the challenges of growing volumes of valuable data scattered in disconnected silos, the organisation successfully implemented Neo4j database and Hume, consolidating data from various sources into a dynamic knowledge graph. The result was a connected view of intelligence, making it easier for analysts to solve crime faster. The partnership between Neo4j and GraphAware in this project demonstrates the transformative impact of graph technology on law enforcement’s ability to leverage growing volumes of valuable data to prevent crime and protect communities.
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product UpdatesNeo4j
David Pond, Lead Product Manager, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
What is OCR Technology and How to Extract Text from Any Image for FreeTwisterTools
Discover the fascinating world of Optical Character Recognition (OCR) technology with our comprehensive presentation. Learn how OCR converts various types of documents, such as scanned paper documents, PDFs, or images captured by a digital camera, into editable and searchable data. Dive into the history, modern applications, and future trends of OCR technology. Get step-by-step instructions on how to extract text from any image online for free using a simple tool, along with best practices for OCR image preparation. Ideal for professionals, students, and tech enthusiasts looking to harness the power of OCR.
Overview of ERP - Mechlin Technologies.pptxMitchell Marsh
This PowerPoint presentation provides a comprehensive overview of Enterprise Resource Planning (ERP) systems. It covers the fundamental concepts, benefits, and key functionalities of ERP software, illustrating how it integrates various business processes into a unified system. From finance and HR to supply chain and customer relationship management, ERP facilitates efficient data management and decision-making across organizations. Whether you're new to ERP or looking to deepen your understanding, this presentation offers valuable insights into leveraging ERP for business success.
A Comparative Analysis of Functional and Non-Functional Testing.pdfkalichargn70th171
A robust software testing strategy encompassing functional and non-functional testing is fundamental for development teams. These twin pillars are essential for ensuring the success of your applications. But why are they so critical?
Functional testing rigorously examines the application's processes against predefined requirements, ensuring they align seamlessly. Conversely, non-functional testing evaluates performance and reliability under load, enhancing the end-user experience.
Ansys Mechanical enables you to solve complex structural engineering problems and make better, faster design decisions. With the finite element analysis (FEA) solvers available in the suite, you can customize and automate solutions for your structural mechanics problems and parameterize them to analyze multiple design scenarios. Ansys Mechanical is a dynamic tool that has a complete range of analysis tools.
Break data silos with real-time connectivity using Confluent Cloud Connectorsconfluent
Connectors integrate Apache Kafka® with external data systems, enabling you to move away from a brittle spaghetti architecture to one that is more streamlined, secure, and future-proof. However, if your team still spends multiple dev cycles building and managing connectors using just open source Kafka Connect, it’s time to consider a faster and cost-effective alternative.
A captivating AI chatbot PowerPoint presentation is made with a striking backdrop in order to attract a wider audience. Select this template featuring several AI chatbot visuals to boost audience engagement and spontaneity. With the aid of this multi-colored template, you may make a compelling presentation and get extra bonuses. To easily elucidate your ideas, choose a typeface with vibrant colors. You can include your data regarding utilizing the chatbot methodology to the remaining half of the template.
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CViewSurvey is a SaaS-based Web & Mobile application that provides digital transformation to traditional paper surveys and feedback for customer & employee experience, field & market research that helps you evaluate your customer's as well as employee's loyalty.
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Lots of bloggers are using Google AdSense now. It’s getting really popular. With AdSense, bloggers can make money by showing ads on their websites. Read this important article written by the experienced designers of the best website designing company in Delhi –
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Graphs for AI – Guess the Future Given the Past
1. 10/07/2019
1
Graphs for AI and ML
Dr. Jim Webber
Chief Scientist, Neo4j
@jimwebber
● Some no-BS definitions
● Graphs and an accidental Skynet
● Graph theory
● Contemporary graph ML
● The future of graph AI
Overview
2. 10/07/2019
2
● ML - Machine Learning
○ Finding functions from historical data to guide future
interactions within a given domain
● AI - Artificial Intelligence
● The property of a system that it appears intelligent to its
users
● Often, but not always, using ML techniques
● Or ML implementations that can be cheaply retrained to
address neighbouring domains
A Bluffer’s Guide to AI-cronyms
● Predictive analytics
● Use past data to predict the future
● General purpose AI
● ML with transfer learning such that learned experiences in
one domain can be applied elsewhere
● Human-like AI
Often conflated with
4. 10/07/2019
4
Extract all the features!
• What do we do? Turn it to
vectors and pump it through a
classification or regression
model
• That’s actually not a bad
thing
• But we can do so much before
we even get to ML…
• … if we have graph data
Credit: Graph Algorithms, Holder and Needham, O’Reilly 2019
6. 10/07/2019
6
stole
from
loves
loves
enemy
enemy
A Good
Man Goes
to War
appeared
in
appeared
in
appeared
in
appeared
in
Victory of
the Daleks
appeared
in
appeared
in
companion
companion
enemy
stole
from
loves
loves
enemy
enemy
A Good
Man Goes
to War
appeared
in
appeared
in
appeared
in
appeared
in
Victory of
the Daleks
appeared
in
appeared
in
companion
companion
enemy
planet
prop
species
species
species
character
character
character
episode
episode
8. 10/07/2019
8
Fearless querying
MATCH path = (:author {name:’Jim Webber’}
-[*]->(:character {name:’The Doctor’})
RETURN path
OR
MATCH (me:author {name:’Jim Webber’},
(doc:character {name:’The Doctor’}),
path = shortestPath((me)-[*]->(doc))
RETURN path
regeneration
character
actor
character
actor
landlord
author
tenant
flat
book
author
wrote
wrote
owns
sublet
played
seriesin
in
played
played
character
played
21. 10/07/2019
21
Search structure
Graph Theory
• Rich knowledge of how graphs
operate in many domains
• Off the shelf algorithms to
process those graphs for
information, insight,
predictions
• Low barrier to entry
• Amazingly powerful
31. 10/07/2019
31
It if a node has strong relationships to two neighbours, then these
neighbours must have at least a weak relationship between them.
[Wikipedia]
Strong Triadic Closure
Triadic Closure
(weak relationship)
name: Kenny
name: Stan name: Cartman
FRIENDFRIEND
32. 10/07/2019
32
Triadic Closure
(weak relationship)
name: Kenny
name: Stan name: Cartman
FRIENDFRIEND
name: Kenny
name: Stan name: Cartman
FRIENDFRIEND
FRIEND 50%
• Relationships can have “strength” as well as intent
• Think: weighting on a relationship in a property graph
• Weak links play another super-important structural role in graph
theory
• They bridge neighbourhoods
Weak relationships
33. 10/07/2019
33
Local Bridges
FRIEND
name: Kenny
name: Stanname: Kyle
FRIENDFRIEND
FRIEND
name: Sally
name: Bebename: Wendy
FRIENDFRIEND
FRIEND 50%
name:
Cartman
FRIEND
FRIEND
50%ENEMY
“If a node A in a network satisfies the Strong Triadic Closure Property
and is involved in at least two strong relationships, then any local
bridge it is involved in must be a weak relationship.”
[Easley and Kleinberg]
Local Bridge Property
34. 10/07/2019
34
University Karate Club
• (NP) Hard problem
• Repeatedly remove the spanning links between dense regions
• Or recursively merge nodes into ever larger “subgraph” nodes
• Choose your algorithm carefully – some are better than others
for a given domain
• Can use to (almost exactly) predict the
break up of the karate club!
Graph Partitioning
38. 10/07/2019
38
Find and stop spammers
Extract graph structure over time
Not message content!
(Fakhraei et al, KDD 2015)
Learning to stop bad guys
Result: find and classify 70% spammers with 90% accuracy
Much of modern graph ML is still about turning graphs to vectors
Graph2Vec and friends
Highly complementary techniques
Mixing structural data and features gives better results
Better data into the model, better results out
But we don’t have to always vectorize graphs...
Graph ML
39. 10/07/2019
39
Knowledge Graphs
• Semantic domain knowledge for
inference and understanding
• E.g. eBay Google Assistant
• What’s the next best question to
ask when a potential customer
says they want a bag?
• Price? Function? Colour?
• Depends on context! Demographic,
history, user journey.
• Richly connected data makes the
system seem intelligent
• But it’s “just” data and algorithms in
reality
Graph Convolutional
Neural Networks
A general architecture for
predicting node and
relationship attributes in
graphs.
(Kipf and Welling, ICLR 2017)
Credit: Andrew Docherty (CSIRO), YowData 2017
https://www.youtube.com/watch?v=Gmxz41L70Fg
40. 10/07/2019
40
Graph Networks for
Structured Causal Models
• Position paper from Google,
MIT, Edinburgh
• Structured representations
and computations (graphs)
are key
• Goal: generalize beyond direct
experience
• Like human infants can
https://arxiv.org/pdf/1806.01261.pdf
credit: @markhneedham