What's Your Story? Finding the Narrative That Sets You Apart
Finding trends in large scale document sets
-
Upload
treparel -
Category
Technology
-
view
639 -
download
0
description
Transcript of Finding trends in large scale document sets
Treparel
Delftechpark 26
2628 XH Delft
The Netherlands
www.treparel.com
Dr. Anton Heijs CEO/CTO
September 24, 2012
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.
Treparel KMX – All rights reserved 2012 3 www.treparel.com
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
Treparel KMX – All rights reserved 2012 5 www.treparel.com
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
Treparel KMX – All rights reserved 2012 6 www.treparel.com
The Intellectual Economy
Past : Selling products finances R&D
Return on investments
Research , Discovery
Development , Manufacturing
Marketing , Sales
Life Cycle Management
Revenues
7
Today: value creation and revenue generation from IP (to finance R&D)
Revenues
Return on investments
Research , Discovery
Development , Manufacturing
Marketing , Sales
Life Cycle Management
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
Treparel KMX – All rights reserved 2012 8 www.treparel.com
• 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
Treparel KMX – All rights reserved 2012 9 www.treparel.com
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
Treparel KMX – All rights reserved 2012 10 www.treparel.com
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
Treparel KMX – All rights reserved 2012 11 www.treparel.com
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
Treparel KMX – All rights reserved 2012 12 www.treparel.com
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
Treparel KMX – All rights reserved 2012 13 www.treparel.com
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
Treparel KMX – All rights reserved 2012 14 www.treparel.com
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
Treparel KMX – All rights reserved 2012 15 www.treparel.com
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
Treparel KMX – All rights reserved 2012 16 www.treparel.com
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
Treparel KMX – All rights reserved 2012 17 www.treparel.com
Auto reporting & analysis for multiple users
• Reporting of aggregated results:
– Pie & bar charts
• Providing overview of the subject:
– landscape visualization
• Enabling rich interaction
Page 18 Treparel KMX – All rights reserved 2012 18 www.treparel.com
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
Treparel KMX – All rights reserved 2012 20 www.treparel.com
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)?
Treparel KMX – All rights reserved 2012 22 www.treparel.com
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
Treparel KMX – All rights reserved 2012 24 www.treparel.com
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
Treparel KMX – All rights reserved 2012 26 www.treparel.com
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
Treparel KMX – All rights reserved 2012 28 www.treparel.com