Government GraphSummit: Leveraging Graphs for AI and ML
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Phani Dathar, Ph.D., Data Science Solution Architect, Neo4j Relationships are highly predictive of behavior. Graph technology abstracts connections in our data so businesses can apply relationships and network structures to make better predictions. Hear about the journey from graph analytics and machine learning to graph-enhanced AI. We’ll also cover how enterprises are using graph data science in areas such as fraud, targeted marketing, healthcare, and recommendations.
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Government GraphSummit: Leveraging Graphs for AI and ML
- 1. © 2022 Neo4j, Inc. All rights reserved. © 2022 Neo4j, Inc. All rights reserved. Phani Dathar, PhD Data Science Solution Architect, Neo4j Leveraging Graphs for AI and ML Relationship-Driven AI
- 2. Neo4j, Inc. All rights reserved 2022 Knowledge Graphs Graph Feature Engineering and Graph ML Graph Analytics, Investigations and Counterfactuals Integrations and Knowledge Graphs for Heuristic AI Capitalize Analysis Data Modeling 2 Graphs enrich all stages of AI ecosystem
- 3. Neo4j, Inc. All rights reserved 2022 3 Let’s start with an example…
- 4. Neo4j, Inc. All rights reserved 2022 4 Graph to Tabular data for ML.. Lamp Lightbulbs Designer Pillow **HE Light bulbs Mingo X Jane X X Aditi X Fabien … …
- 5. Neo4j, Inc. All rights reserved 2022 5 Information without context!! Lamp Lightbulbs Designer Pillow **HE Light bulbs Mingo X Jane X X Aditi X Fabien … … Interior Designers Subsequent Purchases Similar Products
- 6. Neo4j, Inc. All rights reserved 2022 Take advantage of ● graphs to capture the network structure ● graph queries to store and retrieve relationships ● graph algorithms to infer relationships and derive context What can (or should) we do?
- 7. Neo4j, Inc. All rights reserved 2022 Knowledge Graphs Graph Feature Engineering and Graph ML Graph Analytics, Investigations and Counterfactuals Integrations and Knowledge Graphs for Heuristic AI Capitalize Analysis Data Modeling 7 Graphs enrich all stages of AI ecosystem
- 8. Neo4j, Inc. All rights reserved 2022 8 Knowledge graphs
- 9. Neo4j, Inc. All rights reserved 2022 9 Contextual recommendations with Knowledge graphs RECOMMENDER SYSTEM PIPELINE Context
- 10. Neo4j, Inc. All rights reserved 2022 Knowledge Graphs Graph Feature Engineering and Graph ML Graph Analytics, Investigations and Counterfactuals Integrations and Knowledge Graphs for Heuristic AI Capitalize Analysis Data Modeling 10 Graphs enrich all stages of AI ecosystem
- 11. Neo4j, Inc. All rights reserved 2022 11 What are Graph Algorithms?
- 12. Neo4j, Inc. All rights reserved 2022 12 Graph Algorithms in Neo4j GDS Pathfinding & Search • Shortest Path • Single-Source Shortest Path • All Pairs Shortest Path • A* Shortest Path • Yen’s K Shortest Path • Minimum Weight Spanning Tree • K-Spanning Tree (MST) • Random Walk • Breadth & Depth First Search Centrality & Importance • Degree Centrality • Closeness Centrality • Harmonic Centrality • Betweenness Centrality & Approx. • PageRank • Personalized PageRank • ArticleRank • Eigenvector Centrality • Hyperlink Induced Topic Search (HITS) • Influence Maximization (Greedy, CELF) Community Detection • Triangle Count • K-Means • Local Clustering Coefficient • Connected Components (Union Find) • Strongly Connected Components • Label Propagation • Louvain Modularity • K-1 Coloring • Modularity Optimization • Speaker Listener Label Propagation Supervised Machine Learning • Node Classification • Link Prediction • Node Regression … and more! Heuristic Link Prediction • Adamic Adar • Common Neighbors • Preferential Attachment • Resource Allocations • Same Community • Total Neighbors Similarity • Node Similarity • K-Nearest Neighbors (KNN) • Jaccard Similarity • Cosine Similarity • Pearson Similarity • Euclidean Distance • Approximate Nearest Neighbors (ANN) Graph Embeddings • Node2Vec • FastRP • GraphSAGE • Synthetic Graph Generation • Scale Properties • Collapse Paths • One Hot Encoding • Split Relationships • Graph Export • Pregel API (write your own algos)
- 13. Neo4j, Inc. All rights reserved 2022 Graph Feature Engineering 13 Human-crafted query, human-readable result MATCH (p1:Person)-[:ENEMY]->(:Person)<-[:ENEMY]-(p2:PERSON) MERGE (p1)-[:FRIEND]->(p2) AI-learned formula, machine-readable result Predefined formula, human-readable result PageRank(Emil) = 13.25 PageRank(Amy) = 4.83 PageRank(Alicia) = 4.75 Node2Vec(Emil) =[5.4 5.1 2.4 4.5 3.1] Node2Vec(Amy) =[2.8 1.8 7.2 0.9 3.0] Node2Vec(Alicia)=[1.4 5.2 4.4 3.9 3.2] Queries Algorithms Embeddings Machine Learning Workflows Train ML models based on results
- 14. Neo4j, Inc. All rights reserved 2022 14 Enriched Knowledge Graphs Structured Unstructured Ontologies Graph Algorithms and Graph Queries Semantics, Derived relationships and additional context Natural relationships
- 15. Neo4j, Inc. All rights reserved 2022 15 Enrich ML workflows Python Client Built for Data Scientists ● Native Python Client ● 65+ Pretuned Algos ● Single API for load, analysis & writeback ● Production tier graduation
- 16. Neo4j, Inc. All rights reserved 2022 Graph algorithms and graph embeddings are used for generating context and resolving identities/entities Identity Management / Entity Resolution Neo4j APOC Capture relationships between entities across data sources using a knowledge graph Create additional weighted relationships based on similar text description and/or other similar metadata Construct node embeddings and resolve entities based on weighted pairwise similarity between various entities Identify communities of entities based on distance between node embeddings
- 17. Neo4j, Inc. All rights reserved 2022 Knowledge Graphs Graph Feature Engineering and Graph ML Graph Analytics, Investigations and Counterfactuals Integrations and Knowledge Graphs for Heuristic AI Capitalize Analysis Data Modeling 17 Graphs enrich all stages of AI ecosystem
- 18. Neo4j, Inc. All rights reserved 2022 18 Queries Find the patterns you know exist. Machine Learning Uncover trends and make predictions Visualization Explore, collaborate, and explain Graph Data Science Analytics Feature Engineering Data Exploration Graph Data Science Queries Machine Learning Visualization
- 19. Neo4j, Inc. All rights reserved 2022 19 Neo4j Bloom Explore Graphs Visually Prototype Concepts Faster Collaborate Across Teams
- 20. Neo4j, Inc. All rights reserved 2022 20 Ad-hoc Exploration Workflows Search Refine Look for something Visualize Layout Style View results Select Filter Identify subset Expand Pathfind Cluster Aggregate Edit Annotate Act Take an action Save & Share Collaborate Logical graph view Non-functional considerations UI / UX considerations
- 21. Neo4j, Inc. All rights reserved 2022 Knowledge Graphs Graph Feature Engineering and Graph ML Graph Analytics, Investigations and Counterfactuals Integrations and Knowledge Graphs for Heuristic AI Capitalize Analysis Data Modeling 21 Graphs enrich all stages of AI ecosystem
- 22. Neo4j, Inc. All rights reserved 2022 22 Neo4j is part of your data ecosystem DATA SOURCES USE CASES INGEST Apache Hop Structured Unstructured DATA ANALYTICS DATA MANAGEMENT Journey Analytics Risk Analytics Churn Analysis What-if Analysis Feature Engineering & ML Fraud Recommendations Data Fabric Data Compliance Data Governance Data Provenance Data Lineage Next Best Case Ontologies Neo4j Bloom Neo4j GDS Library PRODUCT COMPONENTS APOC VISUALIZE AUTO ML DRIVERS & APIs
- 23. Neo4j, Inc. All rights reserved 2022 23 Integrated architecture for Contextual ML predictions Data Pipeline BI & Analytics ML & Data Science Development ML Deployment & Monitoring Users Web Apps Services Jobs Feature Engineering & Knowledge Graph Data Source Neo4j Database Neo4j GDS in-memory projections Neo4j Graph Data Science BI Connector Bloom Graph Visualization Code Registry Batch Inference Snowflake ETL Neo4j DWH Connector Vertex AI Neo4j GDS Python Recommendation Service Cloud Storage Cloud Scheduler Cloud Composer TensorFlow TensorFlow Cypher
- 24. Neo4j, Inc. All rights reserved 2022 Neo4j, Inc. All rights reserved 2022 Thank You Phani Dathar, PhD Data Science Solution Architect, Neo4j https://www.linkedin.com/in/gopi-dathar Email: Phani.Dathar@Neo4j.com