1. Dr. Kai Simon
Large-Scale Patent Classification
at the European Patent Office

2. ABOUT AVERBIS
Founded: 2007
Location: Freiburg im Breisgau
Team: Domain & IT-Experts
Focus: Leverage structured & unstructured information
Current Sectors: Pharma, Health, Automotive, Publishers & Libraries

3. SELECTED CUSTOMERS

4. PORTFOLIO
Products
Information Discovery Platform
Text Mining Search and Analysis
Terminology
Management

5. PATENT CLASSIFICATION AT EPO
Tender No. 1585
1) Pre-Classification of
unpublished patents into departments
2) Re-Classification on
published patents, if category system changes

6. PATENT CLASSIFICATION AT EPO
Tender No. 1585
1) Pre-Classification of
unpublished patents into departments
Our Motivation:
• Great Classification Use-Case
– Big Data (80 Mio. patents available)
– Large Scale Category System >250.000 CPC codes
– Tough classification quality and response time
constraints
• Text Mining Success Story

7. http://www.epo.org/about-us/annual-reports-statistics/annual-report/2014.html

8. OLD CLASSIFICATION PROCESS
PATENTS CLA SSIFICATION DEPARTMENTS

9. CLASSIFICATION COMPLEXITY
~250.000
CPC Codes
~1.500
Ranges
250
Departments

10. CLASSIFICATION PROCESS
PATENTS CLA SSIFICATION DEPARTMENTS

11. NEW CLASSIFICATION PROCESS
PATENTS CLA SSIFICATION DEPARTMENTS

12. STATUS & OUTLOOK
• Quality Evaluation
[passed]
• Going Live [April]
• Continuous Optimization

13. COME VISIT OUR BOOTH
Products
Information Discovery Platform
Text Mining Search and Analysis
Terminology
Management

14. For further questions, please contact:
Noël Lochtenbergh
& Dr. Kai Simon
 + 49 (0)761 203 97690
 info@averbis.com

15. NUMBER OF STAFF
Status: December 2008

16. SOME FACTS
• about 650k training documents from 2005-2013
• supervised learning: light-weight and fast linear support
vector machine
• Training time (16 Cores, 128 GB RAM)
– Feature Extraction: ~14 minutes
– Training of Classifiers: ~10 minutes
– Classification: < 2 seconds