Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Real World Knowledge Graphs

64 views

Published on

Nav Mathur, Director of Enterprise Solutions, Neo4j

Published in: Software
  • Be the first to comment

  • Be the first to like this

Real World Knowledge Graphs

  1. 1. A Real-World Guide to Building Your Knowledge Graphs Nav Mathur Sr. Director – Global Solutions, Neo4j, Inc. in/navmathur @nav_mathur
  2. 2. 2 What do these organizations have in Common? 2
  3. 3. 3 More real-world knowledge graphs
  4. 4. 4 Knowledge Graph Vs Knowledge Base “Unlike a simple knowledge base with flat structures and static content, a knowledge graph acquires and integrates adjacent information using data relationships to derive new knowledge.”
  5. 5. Connected around relevant attributes. (contextually related) Dynamically updating / not manual Uses intelligent labelling and ties in to the graph automatically Explainable - Intelligent metadata helps traverse to find answers to specific problems, even when we don’t know exactly how to ask for it. Usually contains heterogeneous data types. It combines and uncovers connections across silos of information. Key Principles of a Knowledge Graph
  6. 6. 6 Financial Services Knowledge Graph Credit Risk Management
  7. 7. 7 Financial Services Knowledge Graph Investment Risk Management
  8. 8. 8 Financial Services Knowledge Graph Portfolio News Recommendations
  9. 9. 9 Portfolio News Recommendations Data Model User Org Article Topic Topic Group HAS_TOPIC GROUP WEIGHT TRACKS REFERENCES IS_AFFILIATED SUPPLIES HAS_ULTIMATE_OWNER HAS_IMMIDIATE_OWNER
  10. 10. 10 Data Orchestration Layer Data Sources CLIENT Admin Dashboard Session Data Feedback Scored Recommen- dations Graph Algorithms AI / ML Click Stream Data INTELLIGENT RECOMMENDATIONS FRAMEWORK Discovery Exclude Boost Diversity User Segmentation Item Similarity Recommendation Engines Building your KG • Modelling • Data Ingestion • Auto Labelling (NLP) • Scoring • Data Lineage • Alerting • Auto and human aided merging/similarity • Integrate ML for refreshing /updating the graph RSS Feed Org. Feed (Graph)
  11. 11. Portfolio News Recommendations Demo
  12. 12. 12 720+ 7/10 12/25 8/10 53K+ 100+ 300+ 450+ Adoption Top Retail Firms Top Financial Firms Top Software Vendors Customers Partners • Creator of the Neo4j Graph Platform • ~250 employees • HQ in Silicon Valley, other offices include London, Munich, Paris and Malmö Sweden • $80M new funding led by Morgan Stanley & One Peak. Total $160M from Fidelity, Sunstone, Conor, Creandum, and Greenbridge Capital • Over 15M+ downloads & container pulls • 300+ enterprise subscription customers with over half with >$1B in revenue Ecosystem Startups in program Enterprise customers Partners Meet up members Events per year Industry’s Largest Dedicated Investment in Graphs Neo4j - The Graph Company
  13. 13. Thank You

×