knowledge graphs for a connected world - ai, deep & machine learning meetup
TRANSCRIPT
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Knowledge Graphsfor a Connected World
March 24, 2016
Benjamin Nussbaum @bennussbaum www.graphgrid.com | www.atomrain.com
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Introduction
Benjamin Nussbaum
20 years of Technology Innovation. Software architecture | Database design | Server infrastructure
President & CTO of AtomRain, one of the world’s leading NEO4J Solution Partners and makers of GraphGrid.
a platform by
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Today’s Meetup Agenda
Knowledge Graphs for a Connected World • What is driving the adoption of graphs
Graph Basics for AI Champions • Where a graph fits within a web 3.0 strategy • Why a graph is the first step to AI • How a graph works
Graph Development for Innovation Teams • Who does what
Graphs in Action • Popular use cases • Putting it all together
Q&A
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A Web of ThingsGenerating a Web of Data
Knowledge Graphs are driving strategies for Web 3.0, The Semantic Web
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A Web of ThingsGenerating a Web of Data
Dynamic Data At Web Scale The Entertainment Graph TM
560 million nodes 1.8 billion relationships 3.0 billion properties
Continuous ingestion from dozens of
external such as Wikipedia, Netflix, Amazon and iTunes for personalized recommendations
and social discovery of content.
The World’s Leading Graph Database
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Brands and Venturesnow have access to graph platform services
Solution Partner
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Brands and Venturesnow have access to graph development partners
Solution Partner
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Today’s Meetup Agenda
Knowledge Graphs for a Connected World • What is driving the adoption of graphs
Graph Basics for AI Champions • Where a graph fits within a web 3.0 strategy • Why a graph is the first step to AI • How a graph works
Graph Development for Innovation Teams • Who does what
Graphs in Action • Popular use cases • Putting it all together
Q&A
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KnowledgeGraph
Big DataIngestion
Real-Time Queries & Algorithms
Pre-Computed Queries & Algorithm
Discovery+ Reasoning
Personalizing Apps Smart Places Interacting Machines
Your Graph is a Data Service to “Smart” Touchpoints
DATA PLATFORM API
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Data Science
Artificial Intelligence
Relating with Interaction
Acting with Processing Layers
Serving with Graphs
Discerning with Patterns
Identify Link Prescribe Do ThinkPredict Sense Adapt
Apps access and updatethe graph Real-Timedata about customers things, and relationships.
Algorithms reasonover the graph Patternsfor best, worst, and next steps or things.
Smart Thingssend machine results to the graph History of a machine’saction and results.
AIsaccess customer insight in the graph Predictionof a customer’snext need or want.
A Graph Manages your Brand’s Evolving Knowledge
Knowledge Graph
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A Graph Records a New Kind of Data
Semantic Web and Knowledge Graphs
Enterprises Systems and Business Transactions
For Business Operations
▪ Business Systems generate data.
▪ Data about BusinessOrders, purchases, invoices,customer interactions…
▪ Static System of Record Standard data; relationships are not first class citizens.
CRM System
Product Catalog
Invoice System
▪ Connected Customers & Smart Thingsgenerate data.
▪ Data about Real-World Concepts, people, places, things, and their relationships.
▪ Dynamic Graph of RelationshipsDiscovers and learns through patterns as relationships change
For Connected Experiences
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A “Node”in the graph
Hotel
RoomPerson
A Graph ModelsReal-World People, Places, and Things
Solution Partner
A “Label”in the graph
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A “Relationship”in the graph
PREFERS
Hotel
RoomPerson
HAS_
AVAI
LABL
E
A Graph ModelsContextual Relationships
Solution Partner
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PREFERS
Hotel
RoomPerson
“Properties”in the graph
lastStayed: 2-10-2015
name: Hilton Hotel
name: Jane Smithnumber: 315
HAS_
AVAI
LABL
E
A Graph Stores and Updates Data about Each Thing and its Relationships
Solution Partner
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PREFERS
Hotel
RoomPerson
Queriestraverse the graph to discoverrelevant resources
For Jane’s preferred hoteland travel destination, identify available rooms,present information to her app.
HAS_
AVAI
LABL
E
Algorithms calculate to solve problems
- Spot Patterns.- Prescribe Best Solution.- Predict Results.
Queries and AlgorithmsReason over the Graph
Solution Partner
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Graph QueriesStart with one “entity” and traverse the graph
to discover linked people, places, or things
Query for a Graph
MATCH (boss)-[:MANAGES*0..3]->(sub),
(sub)-[:MANAGES*1..3]->(report) WHERE boss.name = “John Doe”RETURN sub.name AS Subordinate, count(report) AS Total
NEO4J Cypher Language
“Complex Join” in SQL
Solution Partner
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Example: Calculates the shortest path—the least number of nodes, relationships—between two nodes
Traversal AlgorithmsNavigate the graph and calculate to spot patterns or solve problems
Solution Partner
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Today’s Meetup Agenda
Knowledge Graphs for a Connected World • What is driving the adoption of graphs
Graph Basics for AI Champions • Where a graph fits within a web 3.0 strategy • Why a graph is the first step to AI • How a graph works
Graph Development for Innovation Teams • Who does what
Graphs in Action • Popular use cases • Putting it all together
Q&A
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Subject Matter Experts work with Graph Expertsto create the conceptual model
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Graph Software Engineerscreate the software solution to transform and load data into the graph model
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Multidisciplinary Teamensures the quality of queries and algorithms
User Results
Ongoing Lab: • Subject Matter Experts
(i.e Marketing) • Data Engineer • Algorithm Developer
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KnowledgeGraph
Big DataIngestion
Real-Time Queries & Algorithms
Pre-Computed Queries & Algorithm
Discovery+ Reasoning
DATA PLATFORM
Platform Expertsmanage the scaling platform
Top Challenges
1. Query Performance 2. Algorithm Performance
3. Graph Operation at Scale
4. Server Infrastructure at Scale
5. Ingestion Engines 6. Entity Resolution
API
An enterprise-grade, internet scale data management platform
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Today’s Meetup Agenda
Knowledge Graphs for a Connected World • What is driving the adoption of graphs
Graph Basics for AI Champions • Where a graph fits within a web 3.0 strategy • Why a graph is the first step to AI • How a graph works
Graph Development for Innovation Teams • Who does what
Graphs in Action • Popular use cases • Putting it all together
Q&A
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Master Data ManagementFor customer interests, product lines, store locations, org charts…
For white papers, visit neo4j.com/use-cases/
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Identify & Access ManagementValidates who you are, what group you belong to, and what you’re permitted to
do.
For white papers, visit neo4j.com/use-cases/
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Graph Based SearchDelivers a structured result: such as a song, music attributes, artist, album, and
playlists.
For white papers, visit neo4j.com/use-cases/
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Real time RecommendationsBased on past purchases, recent browsing, or friends’ purchases.
For white papers, visit neo4j.com/use-cases/
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Social NetworkFamily, friend and follower relationships
reveal influencers, peer groups, and patterns of social behavior.
For white papers, visit neo4j.com/use-cases/
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Fraud DetectionUncovers fraud rings and patterns of unusual customer behavior.
For white papers, visit neo4j.com/use-cases/
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Putting it all together: A Connected Fitness Venture
PERSONA GOALS AND PREFERENCES • Skill Level
• Health Conditions
• Workout Goals
• Eating Goals
• Muscle Groups
• Body Areas
• Workout Types
• Supplement Needs
CONSUMER WANTS 1. What fitness programs are best to help me accomplish my workout goals?
2. Which nutritional supplements will help me achieve my eating and workout goals?
3. Who in the community can I work out with and which workout would be good to do together?
Scoring Algorithm considers importances the user places on each item
For Complete Review with Sample Querieshttp://neo4j.com/graphgist/95f4f165-0172-4b3d-981b-edcbab2e0a4b
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BRAND’s WEB OF EVERYTHING • Supplement lines
• Fitness programs
• Social network
Putting it all together: A Connected Fitness Venture
For Complete Review with Sample Querieshttp://neo4j.com/graphgist/95f4f165-0172-4b3d-981b-edcbab2e0a4b
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Product Cross-Selling aligned to users’ personal goals—and results
Putting it all together: A Connected Fitness Venture
For Complete Review with Sample Querieshttp://neo4j.com/graphgist/95f4f165-0172-4b3d-981b-edcbab2e0a4b
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Today’s Meetup Agenda
Knowledge Graphs for a Connected World • What is driving the adoption of graphs
Graph Basics for AI Champions • Where a graph fits within a web 3.0 strategy • Why a graph is the first step to AI • How a graph works
Graph Development for Innovation Teams • Who does what
Graphs in Action • Popular use cases • Putting it all together
Q&A
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Q&A What do you think about Graphs?
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Thank You! Knowledge Graphs for a Connected World
March 24, 2016
Benjamin Nussbaum @bennussbaum www.graphgrid.com | www.atomrain.com