Knowledge Graphs for a Connected World - AI, Deep & Machine Learning Meetup

Knowledge Graphsfor a Connected World

March 24, 2016

Benjamin Nussbaum @bennussbaum www.graphgrid.com | www.atomrain.com

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

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

A Web of ThingsGenerating a Web of Data

Knowledge Graphs are driving strategies for Web 3.0, The Semantic Web

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

Brands and Venturesnow have access to graph platform services

Solution Partner

Brands and Venturesnow have access to graph development partners

Solution Partner






Q&A

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

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

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

A “Node”in the graph

Hotel

RoomPerson

A Graph ModelsReal-World People, Places, and Things

Solution Partner

A “Label”in the graph

A “Relationship”in the graph

PREFERS

Hotel

RoomPerson

HAS_

AVAI

LABL

E

A Graph ModelsContextual Relationships

Solution Partner

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

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

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

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






Q&A

Subject Matter Experts work with Graph Expertsto create the conceptual model

Graph Software Engineerscreate the software solution to transform and load data into the graph model

Multidisciplinary Teamensures the quality of queries and algorithms

User Results

Ongoing Lab: • Subject Matter Experts

(i.e Marketing) • Data Engineer • Algorithm Developer

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






Q&A

Master Data ManagementFor customer interests, product lines, store locations, org charts…

For white papers, visit neo4j.com/use-cases/

Identify & Access ManagementValidates who you are, what group you belong to, and what you’re permitted to

do.


Graph Based SearchDelivers a structured result: such as a song, music attributes, artist, album, and

playlists.


Real time RecommendationsBased on past purchases, recent browsing, or friends’ purchases.


Social NetworkFamily, friend and follower relationships

reveal influencers, peer groups, and patterns of social behavior.


Fraud DetectionUncovers fraud rings and patterns of unusual customer behavior.


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

BRAND’s WEB OF EVERYTHING • Supplement lines

• Fitness programs

• Social network



Product Cross-Selling aligned to users’ personal goals—and results








Q&A

Q&A What do you think about Graphs?

Thank You! Knowledge Graphs for a Connected World

March 24, 2016

Benjamin Nussbaum @bennussbaum www.graphgrid.com | www.atomrain.com

Data & Analytics

Knowledge Graphs for a Connected World - AI, Deep & Machine Learning Meetup