SlideShare a Scribd company logo
1 of 35
1
Graphs & AI
A Path for Enterprise Data Science
Amy Hodler @amyhodler
Director, Graph Analytics & AI Programs
Neo4j
How Graphs are Changing AI
Relationships
The Strongest Predictors of Behavior!
“Increasingly we're learning that you can make
better predictions about people by getting all the
information from their friends and their friends’
friends than you can from the information you have
about the person themselves”
James Fowler
11
Predicting Financial Contagion
From Global to Local
12
Graph Is Accelerating AI Innovation
13
4,000
3,000
2,000
1,000
0
2010 2011 2012 2013 2014 2015 2016 2017 2018
Graph Technology
Mentioned
graph neural network
graph convolutional
graph embedding
graph learning
graph attention
graph kernel
graph completion
AI Research Papers Featuring Graph
Source: Dimension Knowledge System
Predictive
Maintenance
Churn
Prediction
Fraud
Detection
Life SciencesRecommendations
Cybersecurity
Customer
Segmentation
Search/MDM
Graph Data Science Applications
Better Predictions with Graphs
Using the Data You Already Have
• Current data science models ignore network structure
• Graphs add highly predictive features to ML models, increasing accuracy
• Otherwise unattainable predictions based on relationships
Machine Learning Pipeline
15
Goals of Graph Data Science
Better
Decisions
Higher
Accuracy
New Learning
and More Trust
16
Decision
Support
Graph Based
Prediction
Graph Native
Learning
The Path of Graph Data Science
Decision Support Graph Based
Prediction
Graph Native Learning
17
Graph Feature
Engineering
Graph
Embeddings
Graph Neural
Networks
Knowledge
Graphs
Graph
Analytics
The Path of Graph Data Science
Graph Feature
Engineering
Graph
Embeddings
Graph Neural
Networks
18
Graph
AnalyticsKnowledge
Graphs
Graph search
and queries
Support domain
experts
Knowledge Graph with Queries
Connecting the Dots has become...
19
Multiple graph layers of financial information
Includes corporate data with cross-relationships and external news
Knowledge Graph with Queries
Connecting the Dots
Dashboards and tools
• Credit risk
• Investment risk
• Portfolio news recommendations
• Typical analyst portfolio is 200 companies
• Custom relative weights
1 Week Snapshot:
800,000 shortest path calculations for the ranked
newsfeed. Each calculation optimized to take
approximately 10 ms.
has become...
20
The Path of Graph Data Science
Graph Feature
Engineering
Graph
Embeddings
Graph Neural
Networks
21
Knowledge
Graphs
Graph
Analytics
Graph queries &
algorithms for offline
analysis
Understanding
Structures
Query
(e.g. Cypher/Python)
Fast, local decisioning
and pattern matching
Graph Algorithms
(e.g. Neo4j library, GraphX)
Global analysis
and iterations
You know what you’re looking
for and
making a decision
You’re learning the overall structure of a
network, updating data, and predicting
Local Patterns Global Computation
22
Deceptively Simple Queries
How many flagged accounts are in the applicant’s
network 4+ hops out?
How many login / account variables in
common?
Add these metrics to your approval process
Difficult for RDMS systems over 3 hops
Graph Analytics via Queries
Detecting Financial Fraud
Improving existing pipelines to identify fraud via heuristics
23
Graph Analytics via Algorithms
Generally Unsupervised
24
A subset of data science algorithms that come from network science,
Graph Algorithms enable reasoning about network structure.
Pathfinding
and Search
Centrality
(Importance)
Community Detection Heuristic
Link Prediction
Similarity
• Euclidean Distance
• Cosine Similarity
• Jaccard Similarity
• Overlap Similarity
• Pearson Similarity
• Approximate KNN
• Degree Centrality
• Closeness Centrality
• CC Variations: Harmonic, Dangalchev,
Wasserman & Faust
• Betweenness Centrality
• Approximate Betweenness Centrality
• PageRank
• Personalized PageRank
• ArticleRank
• Eigenvector Centrality
• Triangle Count
• Clustering Coefficients
• Connected Components (Union Find)
• Strongly Connected Components
• Label Propagation
• Louvain Modularity
• Balanced Triad (identification)
+45 Graph Algorithms in Neo4j
• Parallel Breadth First Search
• Parallel Depth First Search
• Shortest Path
• Single-Source Shortest Path
• All Pairs Shortest Path
• Minimum Spanning Tree
• A* Shortest Path
• Yen’s K Shortest Path
• K-Spanning Tree (MST)
• Random Walk
• Degree Centrality
• Closeness Centrality
• CC Variations: Harmonic, Dangalchev,
Wasserman & Faust
• Betweenness Centrality
• Approximate Betweenness Centrality
• PageRank
• Personalized PageRank
• ArticleRank
• Eigenvector Centrality
• Triangle Count
• Clustering Coefficients
• Connected Components (Union Find)
• Strongly Connected Components
• Label Propagation
• Louvain Modularity
• Balanced Triad (identification)
• Euclidean Distance
• Cosine Similarity
• Jaccard Similarity
• Overlap Similarity
• Pearson Similarity
• Approximate KNN
Pathfinding
& Search
Centrality /
Importance
Community
Detection
Similarity
Link
Prediction
• Adamic Adar
• Common Neighbors
• Preferential Attachment
• Resource Allocations
• Same Community
• Total Neighbors25
There is significant demand for graph
algorithms. Neo4j will be the first
enterprise grade way to run them.
The Path of Graph Data Science
Graph
Embeddings
Graph Neural
Networks
26
Knowledge
Graphs
Graph
Analytics
Graph Feature
Engineering
Graph algorithms &
queries for machine
learning
Improve Prediction
Accuracy
Graph Feature Engineering
Feature Engineering is how we combine and process the data to create
new, more meaningful features, such as clustering or connectivity
metrics.
Graph features add more dimensions to machine
learning
EXTRACTION
27
Feature Engineering using Graph Queries
Telecom-churn prediction
Churn prediction research has found
that simple hand-engineered features
are highly predictive
• How many calls/texts has an
account made?
• How many of their contacts have
churned?
30
Feature Engineering using Graph Queries
Telecom-churn prediction
Add connected features based on graph queries to tabular data
Raw Data:
Call Detail Records
Input Data:
CDR Sample
Call Stats by: Incoming
Outgoing
Per day
Short durations
In-network
Centrality
SMS’s
…
Test/Training Data
Caller ID
Receiver ID
Time
Duration
Location
…
Caller ID
Receiver ID
Time
Duration
Location
…
Identify Early Predictors:
Select simple, interpretable metrics that are
highly correlated w/churn
Churn Score:
Supervised learning to predict binary &
continuous measures of churn
Output/Results
Random
Sample
Selection
Feature
Engineering
31
Feature Engineering using Graph Queries
Telecom-churn prediction
89.4% Accuracy in Subscriber
Churn Prediction
Raw Data:
Call Detail Records
Input Data:
CDR Sample
Call Stats by: Incoming
Outgoing
Per day
Short durations
In-network
Centrality
SMS’s
…
Test/Training Data
Caller ID
Receiver ID
Time
Duration
Location
…
Caller ID
Receiver ID
Time
Duration
Location
…
Identify Early Predictors:
Select simple, interpretable metrics that are
highly correlated w/churn
Churn Score:
Supervised learning to predict binary &
continuous measures of churn
Output/Results
Random
Sample
Selection
Feature
Engineering
Source: Behavioral Modeling for Churn Prediction by Khan et al, 2015
Feature Engineering using Graph Algorithms
Detecting Financial Fraud
Using Structure to
Improve ML Predictions
Connected components
identify disjointed group sharing identifiers
PageRank to measure influence and
transaction volumes
Louvain to identify communities that
frequently interact
Jaccard to measure account similarity
The Path of Graph Data Science
Graph Feature
Engineering
Graph Neural
Networks
33
Knowledge
Graphs
Graph
Analytics
Graph
Embeddings
Graph embedding
algorithms for
ML features
Predictions on complex
structures
Embedding transforms graphs into a feature vector, or set of vectors, describing
topology, connectivity, or attributes of nodes
and relationships in the graph
Graph Embeddings
• Node embeddings: describe connectivity of each node
• Path embeddings: traversals across the graph
• Graph embeddings: encode an entire graph into a single vector
Phases of Deep Walk Approach
34
Graph Embeddings RECOMMENDATIONS
Explainable Reasoning over
Knowledge Graphs for Recommendations
35
Pop
Folk
Castle on the Hill
÷ Album
Ed Sheeran
I See FireTony
Shape of You
SungBy IsSingerOf
Interact
Produce
WrittenBy
Derek
Recommendations for
Derek
0.06
0.24
0.24
0.26
0.03
0.30
.63
The Path of Graph Data Science
Graph Feature
Engineering
Graph
Embeddings
36
Knowledge
Graphs
Graph
Analytics
Graph Neural
Networks
ML within a Graph
New learning methods
“Graphs bring an ability to generalize about
structure that the individual neural nets don't have.”
don't have.”
Next Major Advancement in AI: Graph Native Learning
Next Major Advancement in AI: Graph Native Learning
38
Implements machine learning in a graph environment
Input data as
a graph
Learns while
preserving transient
states
Output as
a graph
Track and validate AI
decision paths
More accurate with less
data and training
The Path of Graph Data Science
Decision Support Graph Based
Prediction
Graph Native Learning
39
Graph Feature
Engineering
Graph
Embeddings
Graph Neural
Networks
Knowledge
Graphs
Graph
Analytics
Resources
Business – AI Whitepaper
neo4j.com/use-cases/
artificial-intelligence-analytics/
Data Scientists
neo4j.com/sandbox
Developers
neo4j.com/download
neo4j.com/graph-algorithms-book
One Thing
43
“AI is not all about Machine Learning.
Context, structure, and reasoning are
necessary ingredients, and Knowledge
Graphs and Linked Data are key
technologies for this.”
Wais Bashir
Managing Editor, Onyx Advisory
44
Graphs & AI
A Path for Enterprise Data Science
Amy Hodler @amyhodler
Director, Graph Analytics & AI Programs
Neo4j
Graph Data Science
take your analytics one step further
45

More Related Content

What's hot

Data Modeling with Neo4j
Data Modeling with Neo4jData Modeling with Neo4j
Data Modeling with Neo4jNeo4j
 
Knowledge Graphs - The Power of Graph-Based Search
Knowledge Graphs - The Power of Graph-Based SearchKnowledge Graphs - The Power of Graph-Based Search
Knowledge Graphs - The Power of Graph-Based SearchNeo4j
 
Neo4j: The path to success with Graph Database and Graph Data Science
Neo4j: The path to success with Graph Database and Graph Data ScienceNeo4j: The path to success with Graph Database and Graph Data Science
Neo4j: The path to success with Graph Database and Graph Data ScienceNeo4j
 
The Knowledge Graph Explosion
The Knowledge Graph ExplosionThe Knowledge Graph Explosion
The Knowledge Graph ExplosionNeo4j
 
Demystifying Graph Neural Networks
Demystifying Graph Neural NetworksDemystifying Graph Neural Networks
Demystifying Graph Neural NetworksNeo4j
 
Graphs for Finance - AML with Neo4j Graph Data Science
Graphs for Finance - AML with Neo4j Graph Data Science Graphs for Finance - AML with Neo4j Graph Data Science
Graphs for Finance - AML with Neo4j Graph Data Science Neo4j
 
The Data Platform for Today’s Intelligent Applications
The Data Platform for Today’s Intelligent ApplicationsThe Data Platform for Today’s Intelligent Applications
The Data Platform for Today’s Intelligent ApplicationsNeo4j
 
GSK: How Knowledge Graphs Improve Clinical Reporting Workflows
GSK: How Knowledge Graphs Improve Clinical Reporting WorkflowsGSK: How Knowledge Graphs Improve Clinical Reporting Workflows
GSK: How Knowledge Graphs Improve Clinical Reporting WorkflowsNeo4j
 
EY: Why graph technology makes sense for fraud detection and customer 360 pro...
EY: Why graph technology makes sense for fraud detection and customer 360 pro...EY: Why graph technology makes sense for fraud detection and customer 360 pro...
EY: Why graph technology makes sense for fraud detection and customer 360 pro...Neo4j
 
Natural Language Processing with Graph Databases and Neo4j
Natural Language Processing with Graph Databases and Neo4jNatural Language Processing with Graph Databases and Neo4j
Natural Language Processing with Graph Databases and Neo4jWilliam Lyon
 
Danish Business Authority: Explainability and causality in relation to ML Ops
Danish Business Authority: Explainability and causality in relation to ML OpsDanish Business Authority: Explainability and causality in relation to ML Ops
Danish Business Authority: Explainability and causality in relation to ML OpsNeo4j
 
Graphs for Data Science and Machine Learning
Graphs for Data Science and Machine LearningGraphs for Data Science and Machine Learning
Graphs for Data Science and Machine LearningNeo4j
 
Ethics in Data Science and Machine Learning
Ethics in Data Science and Machine LearningEthics in Data Science and Machine Learning
Ethics in Data Science and Machine LearningHJ van Veen
 
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...Neo4j
 
The Case for Graphs in Supply Chains
The Case for Graphs in Supply ChainsThe Case for Graphs in Supply Chains
The Case for Graphs in Supply ChainsNeo4j
 
Data Visualization Tips & Tricks
Data Visualization Tips & TricksData Visualization Tips & Tricks
Data Visualization Tips & TricksKoenVerbeeck
 
Neo4j Data Science Presentation
Neo4j Data Science PresentationNeo4j Data Science Presentation
Neo4j Data Science PresentationMax De Marzi
 
Slides: Knowledge Graphs vs. Property Graphs
Slides: Knowledge Graphs vs. Property GraphsSlides: Knowledge Graphs vs. Property Graphs
Slides: Knowledge Graphs vs. Property GraphsDATAVERSITY
 
Knowledge Graphs for Transformation: Dynamic Context for the Intelligent Ente...
Knowledge Graphs for Transformation: Dynamic Context for the Intelligent Ente...Knowledge Graphs for Transformation: Dynamic Context for the Intelligent Ente...
Knowledge Graphs for Transformation: Dynamic Context for the Intelligent Ente...Neo4j
 
Build Intelligent Fraud Prevention with Machine Learning and Graphs
Build Intelligent Fraud Prevention with Machine Learning and GraphsBuild Intelligent Fraud Prevention with Machine Learning and Graphs
Build Intelligent Fraud Prevention with Machine Learning and GraphsNeo4j
 

What's hot (20)

Data Modeling with Neo4j
Data Modeling with Neo4jData Modeling with Neo4j
Data Modeling with Neo4j
 
Knowledge Graphs - The Power of Graph-Based Search
Knowledge Graphs - The Power of Graph-Based SearchKnowledge Graphs - The Power of Graph-Based Search
Knowledge Graphs - The Power of Graph-Based Search
 
Neo4j: The path to success with Graph Database and Graph Data Science
Neo4j: The path to success with Graph Database and Graph Data ScienceNeo4j: The path to success with Graph Database and Graph Data Science
Neo4j: The path to success with Graph Database and Graph Data Science
 
The Knowledge Graph Explosion
The Knowledge Graph ExplosionThe Knowledge Graph Explosion
The Knowledge Graph Explosion
 
Demystifying Graph Neural Networks
Demystifying Graph Neural NetworksDemystifying Graph Neural Networks
Demystifying Graph Neural Networks
 
Graphs for Finance - AML with Neo4j Graph Data Science
Graphs for Finance - AML with Neo4j Graph Data Science Graphs for Finance - AML with Neo4j Graph Data Science
Graphs for Finance - AML with Neo4j Graph Data Science
 
The Data Platform for Today’s Intelligent Applications
The Data Platform for Today’s Intelligent ApplicationsThe Data Platform for Today’s Intelligent Applications
The Data Platform for Today’s Intelligent Applications
 
GSK: How Knowledge Graphs Improve Clinical Reporting Workflows
GSK: How Knowledge Graphs Improve Clinical Reporting WorkflowsGSK: How Knowledge Graphs Improve Clinical Reporting Workflows
GSK: How Knowledge Graphs Improve Clinical Reporting Workflows
 
EY: Why graph technology makes sense for fraud detection and customer 360 pro...
EY: Why graph technology makes sense for fraud detection and customer 360 pro...EY: Why graph technology makes sense for fraud detection and customer 360 pro...
EY: Why graph technology makes sense for fraud detection and customer 360 pro...
 
Natural Language Processing with Graph Databases and Neo4j
Natural Language Processing with Graph Databases and Neo4jNatural Language Processing with Graph Databases and Neo4j
Natural Language Processing with Graph Databases and Neo4j
 
Danish Business Authority: Explainability and causality in relation to ML Ops
Danish Business Authority: Explainability and causality in relation to ML OpsDanish Business Authority: Explainability and causality in relation to ML Ops
Danish Business Authority: Explainability and causality in relation to ML Ops
 
Graphs for Data Science and Machine Learning
Graphs for Data Science and Machine LearningGraphs for Data Science and Machine Learning
Graphs for Data Science and Machine Learning
 
Ethics in Data Science and Machine Learning
Ethics in Data Science and Machine LearningEthics in Data Science and Machine Learning
Ethics in Data Science and Machine Learning
 
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...
Optimizing the Supply Chain with Knowledge Graphs, IoT and Digital Twins_Moor...
 
The Case for Graphs in Supply Chains
The Case for Graphs in Supply ChainsThe Case for Graphs in Supply Chains
The Case for Graphs in Supply Chains
 
Data Visualization Tips & Tricks
Data Visualization Tips & TricksData Visualization Tips & Tricks
Data Visualization Tips & Tricks
 
Neo4j Data Science Presentation
Neo4j Data Science PresentationNeo4j Data Science Presentation
Neo4j Data Science Presentation
 
Slides: Knowledge Graphs vs. Property Graphs
Slides: Knowledge Graphs vs. Property GraphsSlides: Knowledge Graphs vs. Property Graphs
Slides: Knowledge Graphs vs. Property Graphs
 
Knowledge Graphs for Transformation: Dynamic Context for the Intelligent Ente...
Knowledge Graphs for Transformation: Dynamic Context for the Intelligent Ente...Knowledge Graphs for Transformation: Dynamic Context for the Intelligent Ente...
Knowledge Graphs for Transformation: Dynamic Context for the Intelligent Ente...
 
Build Intelligent Fraud Prevention with Machine Learning and Graphs
Build Intelligent Fraud Prevention with Machine Learning and GraphsBuild Intelligent Fraud Prevention with Machine Learning and Graphs
Build Intelligent Fraud Prevention with Machine Learning and Graphs
 

Similar to How Graphs are Changing AI

GraphTour 2020 - Graphs & AI: A Path for Data Science
GraphTour 2020 - Graphs & AI: A Path for Data ScienceGraphTour 2020 - Graphs & AI: A Path for Data Science
GraphTour 2020 - Graphs & AI: A Path for Data ScienceNeo4j
 
GraphTour London 2020 - Graphs for AI, Amy Hodler
GraphTour London 2020  - Graphs for AI, Amy HodlerGraphTour London 2020  - Graphs for AI, Amy Hodler
GraphTour London 2020 - Graphs for AI, Amy HodlerNeo4j
 
Leveraging Graphs for Better AI
Leveraging Graphs for Better AILeveraging Graphs for Better AI
Leveraging Graphs for Better AINeo4j
 
How Graphs Enhance AI
How Graphs Enhance AIHow Graphs Enhance AI
How Graphs Enhance AINeo4j
 
Leveraging Graphs for Better AI
Leveraging Graphs for Better AILeveraging Graphs for Better AI
Leveraging Graphs for Better AINeo4j
 
Leveraging Graphs for AI and ML - Alicia Frame, Neo4j
Leveraging Graphs for AI and ML - Alicia Frame, Neo4jLeveraging Graphs for AI and ML - Alicia Frame, Neo4j
Leveraging Graphs for AI and ML - Alicia Frame, Neo4jNeo4j
 
Improve ml predictions using graph algorithms (webinar july 23_19).pptx
Improve ml predictions using graph algorithms (webinar july 23_19).pptxImprove ml predictions using graph algorithms (webinar july 23_19).pptx
Improve ml predictions using graph algorithms (webinar july 23_19).pptxNeo4j
 
What Is GDS and Neo4j’s GDS Library
What Is GDS and Neo4j’s GDS LibraryWhat Is GDS and Neo4j’s GDS Library
What Is GDS and Neo4j’s GDS LibraryNeo4j
 
3. Relationships Matter: Using Connected Data for Better Machine Learning
3. Relationships Matter: Using Connected Data for Better Machine Learning3. Relationships Matter: Using Connected Data for Better Machine Learning
3. Relationships Matter: Using Connected Data for Better Machine LearningNeo4j
 
Transforming AI with Graphs: Real World Examples using Spark and Neo4j
Transforming AI with Graphs: Real World Examples using Spark and Neo4jTransforming AI with Graphs: Real World Examples using Spark and Neo4j
Transforming AI with Graphs: Real World Examples using Spark and Neo4jFred Madrid
 
Transforming AI with Graphs: Real World Examples using Spark and Neo4j
Transforming AI with Graphs: Real World Examples using Spark and Neo4jTransforming AI with Graphs: Real World Examples using Spark and Neo4j
Transforming AI with Graphs: Real World Examples using Spark and Neo4jDatabricks
 
Graph Algorithms for Developers
Graph Algorithms for DevelopersGraph Algorithms for Developers
Graph Algorithms for DevelopersNeo4j
 
Neo4j Graph Data Science - Webinar
Neo4j Graph Data Science - WebinarNeo4j Graph Data Science - Webinar
Neo4j Graph Data Science - WebinarNeo4j
 
Improving Machine Learning using Graph Algorithms
Improving Machine Learning using Graph AlgorithmsImproving Machine Learning using Graph Algorithms
Improving Machine Learning using Graph AlgorithmsNeo4j
 
Graph Data Science: The Secret to Accelerating Innovation with AI/ML
Graph Data Science: The Secret to Accelerating Innovation with AI/MLGraph Data Science: The Secret to Accelerating Innovation with AI/ML
Graph Data Science: The Secret to Accelerating Innovation with AI/MLNeo4j
 
Graph analytic and machine learning
Graph analytic and machine learningGraph analytic and machine learning
Graph analytic and machine learningStanley Wang
 
El camino hacia el éxito con las bases de datos de grafos, la ciencia de dato...
El camino hacia el éxito con las bases de datos de grafos, la ciencia de dato...El camino hacia el éxito con las bases de datos de grafos, la ciencia de dato...
El camino hacia el éxito con las bases de datos de grafos, la ciencia de dato...Neo4j
 
Neo4j for Healthcare & Life Sciences
Neo4j for Healthcare & Life SciencesNeo4j for Healthcare & Life Sciences
Neo4j for Healthcare & Life SciencesNeo4j
 
Using Connected Data and Graph Technology to Enhance Machine Learning and Art...
Using Connected Data and Graph Technology to Enhance Machine Learning and Art...Using Connected Data and Graph Technology to Enhance Machine Learning and Art...
Using Connected Data and Graph Technology to Enhance Machine Learning and Art...Neo4j
 
GraphSummit London Feb 2024 - ABK - Neo4j Product Vision and Roadmap.pptx
GraphSummit London Feb 2024 - ABK - Neo4j Product Vision and Roadmap.pptxGraphSummit London Feb 2024 - ABK - Neo4j Product Vision and Roadmap.pptx
GraphSummit London Feb 2024 - ABK - Neo4j Product Vision and Roadmap.pptxNeo4j
 

Similar to How Graphs are Changing AI (20)

GraphTour 2020 - Graphs & AI: A Path for Data Science
GraphTour 2020 - Graphs & AI: A Path for Data ScienceGraphTour 2020 - Graphs & AI: A Path for Data Science
GraphTour 2020 - Graphs & AI: A Path for Data Science
 
GraphTour London 2020 - Graphs for AI, Amy Hodler
GraphTour London 2020  - Graphs for AI, Amy HodlerGraphTour London 2020  - Graphs for AI, Amy Hodler
GraphTour London 2020 - Graphs for AI, Amy Hodler
 
Leveraging Graphs for Better AI
Leveraging Graphs for Better AILeveraging Graphs for Better AI
Leveraging Graphs for Better AI
 
How Graphs Enhance AI
How Graphs Enhance AIHow Graphs Enhance AI
How Graphs Enhance AI
 
Leveraging Graphs for Better AI
Leveraging Graphs for Better AILeveraging Graphs for Better AI
Leveraging Graphs for Better AI
 
Leveraging Graphs for AI and ML - Alicia Frame, Neo4j
Leveraging Graphs for AI and ML - Alicia Frame, Neo4jLeveraging Graphs for AI and ML - Alicia Frame, Neo4j
Leveraging Graphs for AI and ML - Alicia Frame, Neo4j
 
Improve ml predictions using graph algorithms (webinar july 23_19).pptx
Improve ml predictions using graph algorithms (webinar july 23_19).pptxImprove ml predictions using graph algorithms (webinar july 23_19).pptx
Improve ml predictions using graph algorithms (webinar july 23_19).pptx
 
What Is GDS and Neo4j’s GDS Library
What Is GDS and Neo4j’s GDS LibraryWhat Is GDS and Neo4j’s GDS Library
What Is GDS and Neo4j’s GDS Library
 
3. Relationships Matter: Using Connected Data for Better Machine Learning
3. Relationships Matter: Using Connected Data for Better Machine Learning3. Relationships Matter: Using Connected Data for Better Machine Learning
3. Relationships Matter: Using Connected Data for Better Machine Learning
 
Transforming AI with Graphs: Real World Examples using Spark and Neo4j
Transforming AI with Graphs: Real World Examples using Spark and Neo4jTransforming AI with Graphs: Real World Examples using Spark and Neo4j
Transforming AI with Graphs: Real World Examples using Spark and Neo4j
 
Transforming AI with Graphs: Real World Examples using Spark and Neo4j
Transforming AI with Graphs: Real World Examples using Spark and Neo4jTransforming AI with Graphs: Real World Examples using Spark and Neo4j
Transforming AI with Graphs: Real World Examples using Spark and Neo4j
 
Graph Algorithms for Developers
Graph Algorithms for DevelopersGraph Algorithms for Developers
Graph Algorithms for Developers
 
Neo4j Graph Data Science - Webinar
Neo4j Graph Data Science - WebinarNeo4j Graph Data Science - Webinar
Neo4j Graph Data Science - Webinar
 
Improving Machine Learning using Graph Algorithms
Improving Machine Learning using Graph AlgorithmsImproving Machine Learning using Graph Algorithms
Improving Machine Learning using Graph Algorithms
 
Graph Data Science: The Secret to Accelerating Innovation with AI/ML
Graph Data Science: The Secret to Accelerating Innovation with AI/MLGraph Data Science: The Secret to Accelerating Innovation with AI/ML
Graph Data Science: The Secret to Accelerating Innovation with AI/ML
 
Graph analytic and machine learning
Graph analytic and machine learningGraph analytic and machine learning
Graph analytic and machine learning
 
El camino hacia el éxito con las bases de datos de grafos, la ciencia de dato...
El camino hacia el éxito con las bases de datos de grafos, la ciencia de dato...El camino hacia el éxito con las bases de datos de grafos, la ciencia de dato...
El camino hacia el éxito con las bases de datos de grafos, la ciencia de dato...
 
Neo4j for Healthcare & Life Sciences
Neo4j for Healthcare & Life SciencesNeo4j for Healthcare & Life Sciences
Neo4j for Healthcare & Life Sciences
 
Using Connected Data and Graph Technology to Enhance Machine Learning and Art...
Using Connected Data and Graph Technology to Enhance Machine Learning and Art...Using Connected Data and Graph Technology to Enhance Machine Learning and Art...
Using Connected Data and Graph Technology to Enhance Machine Learning and Art...
 
GraphSummit London Feb 2024 - ABK - Neo4j Product Vision and Roadmap.pptx
GraphSummit London Feb 2024 - ABK - Neo4j Product Vision and Roadmap.pptxGraphSummit London Feb 2024 - ABK - Neo4j Product Vision and Roadmap.pptx
GraphSummit London Feb 2024 - ABK - Neo4j Product Vision and Roadmap.pptx
 

More from Neo4j

Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Neo4j
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeNeo4j
 
Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j
 
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j
 
Enabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsEnabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsNeo4j
 
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j
 
Neo4j_Jesus Barrasa_The Art of the Possible with Graph.pptx.pdf
Neo4j_Jesus Barrasa_The Art of the Possible with Graph.pptx.pdfNeo4j_Jesus Barrasa_The Art of the Possible with Graph.pptx.pdf
Neo4j_Jesus Barrasa_The Art of the Possible with Graph.pptx.pdfNeo4j
 
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...Neo4j
 
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AIDeloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AINeo4j
 
Ingka Digital: Linked Metadata by Design
Ingka Digital: Linked Metadata by DesignIngka Digital: Linked Metadata by Design
Ingka Digital: Linked Metadata by DesignNeo4j
 
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24Neo4j
 
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptxGraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptxNeo4j
 
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxEmil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxNeo4j
 
Identification of insulin-resistance genes with Knowledge Graphs topology and...
Identification of insulin-resistance genes with Knowledge Graphs topology and...Identification of insulin-resistance genes with Knowledge Graphs topology and...
Identification of insulin-resistance genes with Knowledge Graphs topology and...Neo4j
 
Novo Nordisk's journey in developing an open-source application on Neo4j
Novo Nordisk's journey in developing an open-source application on Neo4jNovo Nordisk's journey in developing an open-source application on Neo4j
Novo Nordisk's journey in developing an open-source application on Neo4jNeo4j
 
EY: Graphs as Critical Enablers for LLM-based Assistants- the Case of Custome...
EY: Graphs as Critical Enablers for LLM-based Assistants- the Case of Custome...EY: Graphs as Critical Enablers for LLM-based Assistants- the Case of Custome...
EY: Graphs as Critical Enablers for LLM-based Assistants- the Case of Custome...Neo4j
 
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptxThe Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptxNeo4j
 
KUBRICK Graphs: A journey from in vogue to success-ion
KUBRICK Graphs: A journey from in vogue to success-ionKUBRICK Graphs: A journey from in vogue to success-ion
KUBRICK Graphs: A journey from in vogue to success-ionNeo4j
 
SKY Paradigms, change and cake: the steep curve of introducing new technologies
SKY Paradigms, change and cake: the steep curve of introducing new technologiesSKY Paradigms, change and cake: the steep curve of introducing new technologies
SKY Paradigms, change and cake: the steep curve of introducing new technologiesNeo4j
 
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...Neo4j
 

More from Neo4j (20)

Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!Webinar - IA generativa e grafi Neo4j: RAG time!
Webinar - IA generativa e grafi Neo4j: RAG time!
 
IA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG timeIA Generativa y Grafos de Neo4j: RAG time
IA Generativa y Grafos de Neo4j: RAG time
 
Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)Neo4j: Data Engineering for RAG (retrieval augmented generation)
Neo4j: Data Engineering for RAG (retrieval augmented generation)
 
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdfNeo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
Neo4j Graph Summit 2024 Workshop - EMEA - Breda_and_Munchen.pdf
 
Enabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge GraphsEnabling GenAI Breakthroughs with Knowledge Graphs
Enabling GenAI Breakthroughs with Knowledge Graphs
 
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdfNeo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
Neo4j_Anurag Tandon_Product Vision and Roadmap.Benelux.pptx.pdf
 
Neo4j_Jesus Barrasa_The Art of the Possible with Graph.pptx.pdf
Neo4j_Jesus Barrasa_The Art of the Possible with Graph.pptx.pdfNeo4j_Jesus Barrasa_The Art of the Possible with Graph.pptx.pdf
Neo4j_Jesus Barrasa_The Art of the Possible with Graph.pptx.pdf
 
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
SWIFT: Maintaining Critical Standards in the Financial Services Industry with...
 
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AIDeloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
Deloitte & Red Cross: Talk to your data with Knowledge-enriched Generative AI
 
Ingka Digital: Linked Metadata by Design
Ingka Digital: Linked Metadata by DesignIngka Digital: Linked Metadata by Design
Ingka Digital: Linked Metadata by Design
 
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
Discover Neo4j Aura_ The Future of Graph Database-as-a-Service Workshop_3.13.24
 
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptxGraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
GraphSummit Copenhagen 2024 - Neo4j Vision and Roadmap.pptx
 
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptxEmil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
Emil Eifrem at GraphSummit Copenhagen 2024 - The Art of the Possible.pptx
 
Identification of insulin-resistance genes with Knowledge Graphs topology and...
Identification of insulin-resistance genes with Knowledge Graphs topology and...Identification of insulin-resistance genes with Knowledge Graphs topology and...
Identification of insulin-resistance genes with Knowledge Graphs topology and...
 
Novo Nordisk's journey in developing an open-source application on Neo4j
Novo Nordisk's journey in developing an open-source application on Neo4jNovo Nordisk's journey in developing an open-source application on Neo4j
Novo Nordisk's journey in developing an open-source application on Neo4j
 
EY: Graphs as Critical Enablers for LLM-based Assistants- the Case of Custome...
EY: Graphs as Critical Enablers for LLM-based Assistants- the Case of Custome...EY: Graphs as Critical Enablers for LLM-based Assistants- the Case of Custome...
EY: Graphs as Critical Enablers for LLM-based Assistants- the Case of Custome...
 
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptxThe Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
The Art of the Possible with Graph by Dr Jim Webber Neo4j.pptx
 
KUBRICK Graphs: A journey from in vogue to success-ion
KUBRICK Graphs: A journey from in vogue to success-ionKUBRICK Graphs: A journey from in vogue to success-ion
KUBRICK Graphs: A journey from in vogue to success-ion
 
SKY Paradigms, change and cake: the steep curve of introducing new technologies
SKY Paradigms, change and cake: the steep curve of introducing new technologiesSKY Paradigms, change and cake: the steep curve of introducing new technologies
SKY Paradigms, change and cake: the steep curve of introducing new technologies
 
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...
 

Recently uploaded

Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024D Cloud Solutions
 
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostKubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostMatt Ray
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1DianaGray10
 
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXVoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXTarek Kalaji
 
UiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation DevelopersUiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation DevelopersUiPathCommunity
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6DianaGray10
 
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxBuilding AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxUdaiappa Ramachandran
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.YounusS2
 
Bird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemBird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemAsko Soukka
 
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsIgniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsSafe Software
 
NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopBachir Benyammi
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdfPedro Manuel
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Commit University
 
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAAnypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAshyamraj55
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfAijun Zhang
 
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...UbiTrack UK
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfinfogdgmi
 
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?IES VE
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesDavid Newbury
 

Recently uploaded (20)

20150722 - AGV
20150722 - AGV20150722 - AGV
20150722 - AGV
 
Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024Artificial Intelligence & SEO Trends for 2024
Artificial Intelligence & SEO Trends for 2024
 
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCostKubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
KubeConEU24-Monitoring Kubernetes and Cloud Spend with OpenCost
 
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1UiPath Platform: The Backend Engine Powering Your Automation - Session 1
UiPath Platform: The Backend Engine Powering Your Automation - Session 1
 
VoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBXVoIP Service and Marketing using Odoo and Asterisk PBX
VoIP Service and Marketing using Odoo and Asterisk PBX
 
UiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation DevelopersUiPath Community: AI for UiPath Automation Developers
UiPath Community: AI for UiPath Automation Developers
 
UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6UiPath Studio Web workshop series - Day 6
UiPath Studio Web workshop series - Day 6
 
Building AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptxBuilding AI-Driven Apps Using Semantic Kernel.pptx
Building AI-Driven Apps Using Semantic Kernel.pptx
 
Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.Basic Building Blocks of Internet of Things.
Basic Building Blocks of Internet of Things.
 
Bird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystemBird eye's view on Camunda open source ecosystem
Bird eye's view on Camunda open source ecosystem
 
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration WorkflowsIgniting Next Level Productivity with AI-Infused Data Integration Workflows
Igniting Next Level Productivity with AI-Infused Data Integration Workflows
 
NIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 WorkshopNIST Cybersecurity Framework (CSF) 2.0 Workshop
NIST Cybersecurity Framework (CSF) 2.0 Workshop
 
Nanopower In Semiconductor Industry.pdf
Nanopower  In Semiconductor Industry.pdfNanopower  In Semiconductor Industry.pdf
Nanopower In Semiconductor Industry.pdf
 
Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)Crea il tuo assistente AI con lo Stregatto (open source python framework)
Crea il tuo assistente AI con lo Stregatto (open source python framework)
 
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPAAnypoint Code Builder , Google Pub sub connector and MuleSoft RPA
Anypoint Code Builder , Google Pub sub connector and MuleSoft RPA
 
Machine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdfMachine Learning Model Validation (Aijun Zhang 2024).pdf
Machine Learning Model Validation (Aijun Zhang 2024).pdf
 
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
UWB Technology for Enhanced Indoor and Outdoor Positioning in Physiological M...
 
Videogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdfVideogame localization & technology_ how to enhance the power of translation.pdf
Videogame localization & technology_ how to enhance the power of translation.pdf
 
How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?How Accurate are Carbon Emissions Projections?
How Accurate are Carbon Emissions Projections?
 
Linked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond OntologiesLinked Data in Production: Moving Beyond Ontologies
Linked Data in Production: Moving Beyond Ontologies
 

How Graphs are Changing AI

  • 1. 1 Graphs & AI A Path for Enterprise Data Science Amy Hodler @amyhodler Director, Graph Analytics & AI Programs Neo4j
  • 3. Relationships The Strongest Predictors of Behavior! “Increasingly we're learning that you can make better predictions about people by getting all the information from their friends and their friends’ friends than you can from the information you have about the person themselves” James Fowler 11
  • 5. Graph Is Accelerating AI Innovation 13 4,000 3,000 2,000 1,000 0 2010 2011 2012 2013 2014 2015 2016 2017 2018 Graph Technology Mentioned graph neural network graph convolutional graph embedding graph learning graph attention graph kernel graph completion AI Research Papers Featuring Graph Source: Dimension Knowledge System
  • 7. Better Predictions with Graphs Using the Data You Already Have • Current data science models ignore network structure • Graphs add highly predictive features to ML models, increasing accuracy • Otherwise unattainable predictions based on relationships Machine Learning Pipeline 15
  • 8. Goals of Graph Data Science Better Decisions Higher Accuracy New Learning and More Trust 16 Decision Support Graph Based Prediction Graph Native Learning
  • 9. The Path of Graph Data Science Decision Support Graph Based Prediction Graph Native Learning 17 Graph Feature Engineering Graph Embeddings Graph Neural Networks Knowledge Graphs Graph Analytics
  • 10. The Path of Graph Data Science Graph Feature Engineering Graph Embeddings Graph Neural Networks 18 Graph AnalyticsKnowledge Graphs Graph search and queries Support domain experts
  • 11. Knowledge Graph with Queries Connecting the Dots has become... 19 Multiple graph layers of financial information Includes corporate data with cross-relationships and external news
  • 12. Knowledge Graph with Queries Connecting the Dots Dashboards and tools • Credit risk • Investment risk • Portfolio news recommendations • Typical analyst portfolio is 200 companies • Custom relative weights 1 Week Snapshot: 800,000 shortest path calculations for the ranked newsfeed. Each calculation optimized to take approximately 10 ms. has become... 20
  • 13. The Path of Graph Data Science Graph Feature Engineering Graph Embeddings Graph Neural Networks 21 Knowledge Graphs Graph Analytics Graph queries & algorithms for offline analysis Understanding Structures
  • 14. Query (e.g. Cypher/Python) Fast, local decisioning and pattern matching Graph Algorithms (e.g. Neo4j library, GraphX) Global analysis and iterations You know what you’re looking for and making a decision You’re learning the overall structure of a network, updating data, and predicting Local Patterns Global Computation 22
  • 15. Deceptively Simple Queries How many flagged accounts are in the applicant’s network 4+ hops out? How many login / account variables in common? Add these metrics to your approval process Difficult for RDMS systems over 3 hops Graph Analytics via Queries Detecting Financial Fraud Improving existing pipelines to identify fraud via heuristics 23
  • 16. Graph Analytics via Algorithms Generally Unsupervised 24 A subset of data science algorithms that come from network science, Graph Algorithms enable reasoning about network structure. Pathfinding and Search Centrality (Importance) Community Detection Heuristic Link Prediction Similarity
  • 17. • Euclidean Distance • Cosine Similarity • Jaccard Similarity • Overlap Similarity • Pearson Similarity • Approximate KNN • Degree Centrality • Closeness Centrality • CC Variations: Harmonic, Dangalchev, Wasserman & Faust • Betweenness Centrality • Approximate Betweenness Centrality • PageRank • Personalized PageRank • ArticleRank • Eigenvector Centrality • Triangle Count • Clustering Coefficients • Connected Components (Union Find) • Strongly Connected Components • Label Propagation • Louvain Modularity • Balanced Triad (identification) +45 Graph Algorithms in Neo4j • Parallel Breadth First Search • Parallel Depth First Search • Shortest Path • Single-Source Shortest Path • All Pairs Shortest Path • Minimum Spanning Tree • A* Shortest Path • Yen’s K Shortest Path • K-Spanning Tree (MST) • Random Walk • Degree Centrality • Closeness Centrality • CC Variations: Harmonic, Dangalchev, Wasserman & Faust • Betweenness Centrality • Approximate Betweenness Centrality • PageRank • Personalized PageRank • ArticleRank • Eigenvector Centrality • Triangle Count • Clustering Coefficients • Connected Components (Union Find) • Strongly Connected Components • Label Propagation • Louvain Modularity • Balanced Triad (identification) • Euclidean Distance • Cosine Similarity • Jaccard Similarity • Overlap Similarity • Pearson Similarity • Approximate KNN Pathfinding & Search Centrality / Importance Community Detection Similarity Link Prediction • Adamic Adar • Common Neighbors • Preferential Attachment • Resource Allocations • Same Community • Total Neighbors25 There is significant demand for graph algorithms. Neo4j will be the first enterprise grade way to run them.
  • 18. The Path of Graph Data Science Graph Embeddings Graph Neural Networks 26 Knowledge Graphs Graph Analytics Graph Feature Engineering Graph algorithms & queries for machine learning Improve Prediction Accuracy
  • 19. Graph Feature Engineering Feature Engineering is how we combine and process the data to create new, more meaningful features, such as clustering or connectivity metrics. Graph features add more dimensions to machine learning EXTRACTION 27
  • 20. Feature Engineering using Graph Queries Telecom-churn prediction Churn prediction research has found that simple hand-engineered features are highly predictive • How many calls/texts has an account made? • How many of their contacts have churned?
  • 21. 30 Feature Engineering using Graph Queries Telecom-churn prediction Add connected features based on graph queries to tabular data Raw Data: Call Detail Records Input Data: CDR Sample Call Stats by: Incoming Outgoing Per day Short durations In-network Centrality SMS’s … Test/Training Data Caller ID Receiver ID Time Duration Location … Caller ID Receiver ID Time Duration Location … Identify Early Predictors: Select simple, interpretable metrics that are highly correlated w/churn Churn Score: Supervised learning to predict binary & continuous measures of churn Output/Results Random Sample Selection Feature Engineering
  • 22. 31 Feature Engineering using Graph Queries Telecom-churn prediction 89.4% Accuracy in Subscriber Churn Prediction Raw Data: Call Detail Records Input Data: CDR Sample Call Stats by: Incoming Outgoing Per day Short durations In-network Centrality SMS’s … Test/Training Data Caller ID Receiver ID Time Duration Location … Caller ID Receiver ID Time Duration Location … Identify Early Predictors: Select simple, interpretable metrics that are highly correlated w/churn Churn Score: Supervised learning to predict binary & continuous measures of churn Output/Results Random Sample Selection Feature Engineering Source: Behavioral Modeling for Churn Prediction by Khan et al, 2015
  • 23. Feature Engineering using Graph Algorithms Detecting Financial Fraud Using Structure to Improve ML Predictions Connected components identify disjointed group sharing identifiers PageRank to measure influence and transaction volumes Louvain to identify communities that frequently interact Jaccard to measure account similarity
  • 24. The Path of Graph Data Science Graph Feature Engineering Graph Neural Networks 33 Knowledge Graphs Graph Analytics Graph Embeddings Graph embedding algorithms for ML features Predictions on complex structures
  • 25. Embedding transforms graphs into a feature vector, or set of vectors, describing topology, connectivity, or attributes of nodes and relationships in the graph Graph Embeddings • Node embeddings: describe connectivity of each node • Path embeddings: traversals across the graph • Graph embeddings: encode an entire graph into a single vector Phases of Deep Walk Approach 34
  • 26. Graph Embeddings RECOMMENDATIONS Explainable Reasoning over Knowledge Graphs for Recommendations 35 Pop Folk Castle on the Hill ÷ Album Ed Sheeran I See FireTony Shape of You SungBy IsSingerOf Interact Produce WrittenBy Derek Recommendations for Derek 0.06 0.24 0.24 0.26 0.03 0.30 .63
  • 27. The Path of Graph Data Science Graph Feature Engineering Graph Embeddings 36 Knowledge Graphs Graph Analytics Graph Neural Networks ML within a Graph New learning methods
  • 28. “Graphs bring an ability to generalize about structure that the individual neural nets don't have.” don't have.” Next Major Advancement in AI: Graph Native Learning
  • 29. Next Major Advancement in AI: Graph Native Learning 38 Implements machine learning in a graph environment Input data as a graph Learns while preserving transient states Output as a graph Track and validate AI decision paths More accurate with less data and training
  • 30. The Path of Graph Data Science Decision Support Graph Based Prediction Graph Native Learning 39 Graph Feature Engineering Graph Embeddings Graph Neural Networks Knowledge Graphs Graph Analytics
  • 31. Resources Business – AI Whitepaper neo4j.com/use-cases/ artificial-intelligence-analytics/ Data Scientists neo4j.com/sandbox Developers neo4j.com/download neo4j.com/graph-algorithms-book
  • 33. 43 “AI is not all about Machine Learning. Context, structure, and reasoning are necessary ingredients, and Knowledge Graphs and Linked Data are key technologies for this.” Wais Bashir Managing Editor, Onyx Advisory
  • 34. 44 Graphs & AI A Path for Enterprise Data Science Amy Hodler @amyhodler Director, Graph Analytics & AI Programs Neo4j
  • 35. Graph Data Science take your analytics one step further 45