Finding trends in large scale document sets

Treparel

Delftechpark 26

2628 XH Delft

The Netherlands

www.treparel.com

Dr. Anton Heijs CEO/CTO

[email protected]

September 24, 2012

http://www.treparel.com

mailto:[email protected]

Analysing large patent portfolios: Nothing remains uncovered

Agenda

• Introduction Treparel & KMX Patent Analytics

• How to deal with Big Data in patents?

• Landscape analysis of large patent sets

• Use Cases: SWOT analysis

Fig 1: patent landscape of ebook technologies

Treparel KMX – All rights reserved 2012 2 www.treparel.com

About Treparel

• Treparel is an innovative technology solution provider of

– Big Data Text Analytics and Visualization technology

– Patent Analytics solutions

• KMX is an integrated data analysis toolset which provides

– Fast and accurate insights in large unstructured document sets to allow companies to make better informed decisions.

• KMX software platform

– Strong focus on R&D with university ecosystem

– Over 30 man years of software-development

– Used by knowledge driven organizations in technology, chemical, and life sciences

• Based in Delft, The Netherlands since 2006.


IP landscape trend example: 1970-2007

Alstom GE

Siemens Dong Feng 4

The importance of analytics in IP

Research Discovery Development Market Launch

Life Cycle Management

Decreasing return

Increasing Return Investment

Market, Legal and Competitive Analysis

Patent Analysis

Research Analysis

$

years


Economic changes in the last decades

• Globalization :

– More companies, increased competition, lower margins

– Innovation for shorter product life cycles

– Manufacturing has become a commodity by outsourcing to low wage countries

• The cost of R&D increased but competition leads to price erosion

• Return on R&D investment drives importance for value creation from IP

• Competitive edge of companies shifts from

production-based to knowledge-based


The Intellectual Economy

Past : Selling products finances R&D

Return on investments

Research , Discovery

Development , Manufacturing

Marketing , Sales


Revenues

7

Today: value creation and revenue generation from IP (to finance R&D)

Revenues

Return on investments

Research , Discovery

Development , Manufacturing

Marketing , Sales


Revenues

Innovations

IP Licensing

Treparel KMX – All rights reserved 2012 www.treparel.com

Adapting to economic developments

The New Reality

• IP strategy over time – Increase the value of the IP portfolio

– Maximize the ROI from R&D

• License management – analyze the impact of economic developments

and its effect for the IP strategy

Drivers

• Number of Patent filings is growing

• Growing need to drive revenues from licensing to fund R&D investment

Value from IP portfolio • Protect market share • Save cost for royalties via cross

licensing • Generate income from royalties • Benefit from License Out from

joint ventures or spin-offs


• Economies depend stronger on each other

• Innovation is a driver of economic growth

• Globalization generates many patents from China and South Korea

• The number and complexity of patent filings is growing

Growing need for fast and accurate analysis of large sets of patents

Trends and implications for the future


Getting more insight using less experts

Big Data Paradox: • Limited (human) resources available for in-depth analysis • Growing need for data driven decisions

Growing Data, Faster Insights: Big Data Analytics

Variety Complexity

Velocity Volume


The big data paradox ; more data but less knowledge ‘Information Gap’

1990 1995 2000 2005 2010 2015 2020

0

2

6

8

10

4

Available data

Available experts for supporting decision making

Information Gap

Data driven decisions


Information democracy: Information Creators and Consumers • Creators

– Defines & prepopulate Analysis Pipelines and test it on the data

– Deploys these pipeline using Cloud computing • Required computing capacity can scale up with the business /

analytical needs

• Consumers

– Pre defined analytical reports

– Sharing feedback and input to the results to optimize analysis

Sharing information empowers collaboration


The traditional IP search and analysis

Information Consumer Request Information Information Creator Data

Database Results

Request

The traditional approach: • Each search/analysis request is focussed on a specific question from one user • When the number of request increases this requires more human searchers • When the searches involve analysis of more patents this requires more time • Very specific searches can not be automated • Analysis of large documents sets can be automated – which is an opportunity to

analyse more and become more competitive

Tools


Information democracy: Proactive analysis to search and analysis

Information Consumers Push Information Information Creators Data

Patent Database

Research Database Running

Analytics Pipeline Marketing

Database

Business User

Analyst

Liberate the Information Search, facilitate the discovery process: • The knowledge Creator:

• defines the analysis pipeline and test it on the data • deploys the analyses using cloud computing resources

• Direct access for information consumers for in depth analyses


Liberate more information using new technologies • Enable a small group of experts with tools to set-up IP

analysis pipelines

– Extend the search on request approach with a pro-active analysis approach on large document sets

– Use analysis pipelines to auto generate visualizations in a browser

– Invest in new technology coming from Big Data Analytics

• Give a large group of users access to the internal webpages providing them with rich statistical information and interactive visualizations


Combining proactive analysis with traditional IP search and discovery

Information Consumers Information Information Creators Data

Database

Tools

Patent Database

Research Database

Running Analytics Pipeline

Marketing Database

Analyst

Tailor made Results

Exchange

Information

Personal Request

Business User


Performing small to large scale SWOT analysis

Patent Database

5000 patents 1000 patents 500 patents

Ranking

Queries

Filtering

SWOT analysis example

• What are most important

patents?

• Who owns them? • What is growth of

patents by: • Technology?

• Owner?

• Country?

• Year?

Overview

and details Business

User


Auto reporting & analysis for multiple users

• Reporting of aggregated results:

– Pie & bar charts

• Providing overview of the subject:

– landscape visualization

• Enabling rich interaction


19

Use Case1: SWOT analysis of Ebooks

Fig 2: Overview landscape visualization of 4257 patens

• Perform proactive SWOT analysis of ebooks market

Amazon Kindle – Apple – Samsung/Google and other players

• Who owns what?

• What can we learn from competitive technology landscape? • Why?

• Determine a company/technology position and opportunities

• We do this in KMX by:

1. Query to get patents on electronic paper technology

2. Landscape analysis 3. Classification/Ranking

4. Filter and select subset

5. Iterate step 1-to-5

Treparel KMX – All rights reserved 2012 19

Analysis of ebook technology

Fig 3: Overview landscape visualization of 4257 patents


Use document classification to rank the patents

Fig 4: Ranked patents using a classifier for ebook technology (In purple the selection of relevant

patents for deeper analysis) Treparel KMX – All rights reserved 2012 21 www.treparel.com

Purple = most important patents

Red = least relevant patents

Drill deeper in the data to learn more

Fig 5: Landscape visualization going from 4257 to 1049 to 369 patents

After removing the irrelevant patents we use filtering to

determine: • Who are the important players (assignees, inventors)?

• Where are the important patents filed (countries)?

• What is the trend over time (growth of patents over the years)?


Define the relevant set of patents to identify your strengths & opportunities

Fig 6: Landscape visualization of 369 most important patents in ebook technology Treparel KMX – All rights reserved 2012 23

Purple = most important patents

Red = least relevant patents

The role of language: Clustering of Patents in Chinese text

Fig 7: Patent landscape visualization using the chinese or englisch text


Use Case 2: SWOT Technical & Biological patents

Fig 8: Landscape visualization of 10920 patents

• Perform SWOT analysis in a converging market: analyze claims with mixed

technologies

• Who owns what?

• How does the technology landscape looks like?

• Why ? • Determine a company/technology position and opportunities

• We do this in KMX by:

1. Query to get patents on mechanical/electronic/optics mixed with

biological technology

2. Landscape analysis 3. Classification/Ranking

4. Filter and select subset

5. Iterate step 1-to-5

Treparel KMX – All rights reserved 2012 25

Use Case: SWOT analysis : patents covering multiple technology areas (engineering & biology)

• Patents become more complex to analyse

• Examples: • More detailed claims • Mixed technologies in

the claims

• Obtaining an landscape

overview is then key

• Analysis from the users perspective is essential (classification/ranking)

Fig 9: Landscape visualization of 10920 patents


Patents from total set with biological focus

• Using the text from the title/abstract and claims

• landscape analysis provides overview

• Using document classification to determine sub clusters

• Using classification and ranking to determine the most relevant documents from the users perspective

Fig 10: Landscape visualization of 134 patens

Key takeaways

Global economy demands value generation from an IP strategy

Big Data Paradox: • Limited (human) resources available for in-depth analysis • Growing need for data driven decisions

The information creators (patent searchers) focus on

• Providing proactive information on generic analysis tasks

• Perform specific analysis for single user request

The information consumers (patent council)

• Get knowledge from automated analysis with

interactive capabilities

• Obtain SWOT analysis knowledge of competitors

• Built and optimize patent strategies


Finding trends in large scale document sets

Technology

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