km rfid presentation
TRANSCRIPT
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RFID PATENT ANALYSIS
KNOWLEDGE MANAGEMENT PROJECT
Shilpa Govada | Shirish Kandekar | Rachana Pejaver | John Wahlman
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WHO DID WHAT
Task Shilpa Shirish Rachana John
Data Collection
Data Parsing
Database Loading
Query writing
Bibliometric Analysis
Citation Network Analysis
Co-word and co-author analysis
Literature Review
Final Report and Presentation
2
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INTRODUCTION
3 * As of 19 Feb 2008
1
• The technology behind RFID has been around since the early 1920s.
2
• The first patent to be associated with the abbreviation RFID was granted to Charles Walton in 1983
3
• Since 1983 there have been 3,952 patents that used the term RFID*
4
• The RFID market has grown rapidly and reached $5 billion in sales in 2007 according to research firm IDTechEx
5 • The RFID business is expected to reach $25 billion by 2017
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RESEARCH OBJECTIVES
4
1
• The goal of this project is to conduct original knowledge management research related to RFID patents.
2
• This research will result in competitive intelligence that may be useful to organizations investing in RFID.
3
• Study and analyze the process of technology innovations by local and international enterprises
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LITERATURE REVIEW
Yen-Chun Wu and Tzu-Chin Yen, “RFID technology innovations: the use of
patent data.” International Journal of Manufacturing Technology and
Management Vol. 10 No. 1 (2007): 106-120
H Dou, V Leveille, S Manullang, and JM Dou Jr., “Patent analysis for
competitive technical intelligence and innovative thinking.” Data Science
JournalVol. 4 (2005): 209-236
Chen-Yuan Liu, James ChingyuYang, "Decoding Patent Information Using
Patent Maps." Data Science JournalVol. 7 (2008): 14-22
Leydesdorff, Loet, “The University-Industry Knowledge Relationship:
Analyzing Patents and the Science Base of Technologies.” Journal of the
American Society for Information Science and TechnologyVol. 55 No. 11
(2004): 991-1001
Leydesdorff, Loet, and Lina Hellsten, “Metaphors and Diaphors in Science
Communication: Mapping the Case of Stem-Cell Research.” Science
CommunicationVol. 27 No. 1 (2005): 64-99
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RESEARCH DESIGN
6
USPTO
database
Collected by Keywords
Data Acquisition
Patent Parsing
Loading in the DB
Patent Publication
Patent Importance/
Strength
Average number of
cites
Co-Occurrence
Analysis
Number of Patents
Knowledge Diffusion
Citation Network
Co - Author Analysis
Data acquisition > Patent parsing > Research status analysis
Research Status Analysis
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DATA ACQUISITION
7
United States Patent and Trademark Office
• All patents since 1976 available in full-text
• First patent using RFID term was in 1983
• Searched “Issued Patents” database
• Pulled all 3,952 patents using the term “RFID” with a Perl program
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DATA PARSING
Parsed 3,935 patents with a Java program
Loaded full dataset into MS SQL database
Can join any table to any other table through PatentID
8
Table Attributes Tuples
Assignee 6 3,651
ForeignPatentRef 4 16,145
IntlClass 7 11,511
Inventor 8 10,916
OtherRef 3 24,314
Patent 9 3,935
PatentContent 7 3,935
PatentRef 5 126,359
UsClass 4 16,724
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DATA ATTRIBUTES
Bolded attributes were used in this research
No processing of attributes was necessary
9
Assignee ForeignPatentRef IntlClass Inventor OtherRef Patent PatentContent PatentRef UsClass
PatentID PatentID PatentID PatentID PatentID PatentID PatentID PatentID PatentID
AssigneeName CitedPatentID SectionName LastName Reference IssueDate Abstract CitedPatentID ClassName
City CitedPatentDate ClassName MiddleName Rank Title Claim CitedPatentDate SubClass
State Rank SubClass FirstName ApplicationNo Description CitedAuthor Rank
Country MainGroup City FileDate Title Rank
Rank SubGroup State ApplicationType FileDate
Rank Country Attorney IssueDate
Rank PrimaryExaminer
AssistantExaminer
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RESEARCH STATUS ANALYSIS TECHNIQUES
Patent publication
Number of patents by country in each year
Number of patents by continent in each year
Number of patents by assignee in each year
Number of patents by technology field in each year
Inventors with most patents
Patents most cited
Patent importance and strength
Average number of cites by country
Average number of cites by assignee
Average number of cites by technology fields
Knowledge diffusion
Country citation network analysis
Institution citation network analysis
Technology citation network analysis
Co-author analysis
Co-occurrence analysis
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Findings:
Patent Publication
Number of patents by country in each year
Number of patents by continent in each year
Number of patents by assignee in each year
Number of patents by technology field in each year
Inventors with most patents
Patents most cited
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BASIC STATISTICS
12
3,935 RFID patents were submitted by:
• 1,209 assignees
• 5,843 inventors
• 2,391 primary inventors
• 32 countries
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US is dominant
with 78.3% of all
RFID patents
issued in last
decade
13
TOP 20 COUNTRIES BY PATENTS ISSUED
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US dominance has
accelerated in
recent years
Zoom in on all
countries except
US
14
TOP 20 COUNTRIES BY PATENTS ISSUED
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Excluding the US,
Japan is the leader
with nearly three
times as many
patents as
Germany
15
TOP 20 COUNTRIES BY PATENTS ISSUED
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North America
leads
Asia overtook
Europe in 2007
16
PATENTS ISSUED BY CONTINENT
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Micron
Technology Inc is
leading followed
by IBM
Corporation and
Symbol
Technolgies
17
PATENTS ISSUED BY ASSIGNEE
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Micron
Technology Inc’s
dropped off
dramatically after
2001
IBM, Symbol
Technologies, and
HP have become
leaders in recent
years
18
PATENTS ISSUED BY ASSIGNEE
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PATENTS ISSUED BY TECHNOLOGY FIELD
Communications, Electrical and Registers are leading technology
fields for RFID patents
Communications, Electrical has more patents than all other fields
in the top 10
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Communications,
Electrical has lead
significantly since
1997, but
Registers has
grown rapidly
since 2002
20
PATENTS ISSUED BY TECHNOLOGY FIELD
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INVENTORS WITH MOST PATENTS
John R. Tuttle and Mark E. Tuttle
John works at Micron
Mark used to work at Micron
John cited Mark 39 times
Mark has never cited John
Brothers???
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PATENTS MOST CITED
Patent 5649296 is the most cited RFID patent, yet its
inventor and assignee are not among the top 20
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Findings:
Patent Importance and Strength
Average number of cites by country
Average number of cites by assignee
Average number of cites by technology fields
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BASIC STATISTICS
24
126,359 citations
• 12,442 to RFID patents
• 113,917 to non-RFID patents
Citations from 3,926 distinct RFID patents
Citations to 43,820 distinct patents
• 1,502 distinct RFID patents
• 42,318 distinct non-RFID patents
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AVERAGE NUMBER OF CITES BY COUNTRY
Top 10 countries by patent count
Ranked by the average number of cites
United States has the most cited patents
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AVERAGE NUMBER OF CITES BY ASSIGNEE
Top 10 assignees by patent count
Ranked by the average number of cites
Motorola has the most cited patents
26
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AVERAGE NUMBER OF CITES BY TECHNOLOGY FIELD
Top 10 technology fields by patent count
Ranked by average number of cites
Communications: Directive Radio Wave Systems and Devices
has the highest average number of cites
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Findings:
Knowledge Diffusion
Country citation network analysis
Institution citation network analysis
Technology citation network analysis
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All 32 countries
citing all other
countries
Nodes sized
proportionally to
citation count
Diagram created
in NetDraw
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COUNTRY CITATION NETWORK ANALYSIS
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COUNTRY CITATION NETWORK ANALYSIS
All 32 countries citing all other countries
Diagram created in GraphViz
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COUNTRY CITATION NETWORK ANALYSIS
Showing only links
of 10 or greater
20 countries
Nodes sized
proportionally to
citation count
Diagram created
in NetDraw
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COUNTRY CITATION NETWORK ANALYSIS
Showing only links of 10 or greater
Diagram created in GraphViz
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INSTITUTION CITATION NETWORK ANALYSIS
All assignees with
links of 15 or
greater
Nodes sized
proportionally to
citation count
Node labels sized
proportionally to
citation count
Diagram created
in NetDraw
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INSTITUTION CITATION NETWORK ANALYSIS
Institutions with
links of 15 or
greater
Diagram created
in GraphViz
Micron
IBM
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TECHNOLOGY FIELD CITATION NETWORK ANALYSIS
Technology Fields
with links of 15 or
greater
Nodes sized
proportionally to
citation count
Diagram created
in NetDraw
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TECHNOLOGY FIELD CITATION NETWORK ANALYSIS
Technology Fields with links of 15 or greater
Diagram created in GraphViz
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Findings:
Co-Author Analysis
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CO-AUTHOR ANALYSIS
5,843 authors
26 authors have
20 or more
patents
81 authors have
between 10 and
20 patents
1,576 authors
have less than 10
patents
4,157 authors
have only one
patent
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CO-AUTHOR ANALYSIS
Removed authors
with less than 20
patents
Applied “Spring-
embedding”
layout
Results in five
distinct groupings
of co-authors
Diagram created
in NetDraw
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CO-AUTHOR ANALYSIS
Same as previous; diagram created in GraphViz
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Findings:
Co-Occurrence Analysis
Analysis Procedure
Patent Titles
Patent Abstracts
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CO-OCCURRENCE ANALYSIS PROCEDURE
Step Description Tools
1 Query desired text for analysis MS SQL
2 Build word frequency list TextSTAT-2.exe
3 Remove stop words such as at, be, of, the Stopword.exe
4 Remove very common words such as RFID Manual
5 Remove words occurring less than 50 times Manual
6 Generate co-occurrence matrix Fulltext.exe
7 Generate diagram Pajek.exe
8 Filter to remove weaker correlations Pajex.exe
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Procedure from Loet Leydesdorff of the University of Amsterdam: http://users.fmg.uva.nl/lleydesdorff/software/fulltext/
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PATENT TITLES CO-OCCURRENCE NETWORK
Titles contain
3,756 distinct
words
3,658 unique
words after
removing stop
words
Diagram created
in Pajek using the
Kamada-Kawai
layout
(N Patents = 3,935; Word frequency > 49; 50 words connected at the threshold level of cosine ≥ 0.000).
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PATENT TITLES CO-OCCURRENCE NETWORK
Transformed to
remove lines with
values < .975
Can really start to
see relationships
between words
Diagram created
in Pajek using the
Kamada-Kawai
layout
(N Patents = 3,935; Word frequency > 49; 50 words
connected at the threshold level of cosine ≥ 0.975).
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PATENT ABSTRACTS CO-OCCURRENCE NETWORK
Abstracts contain
12,321 distinct
words
11,680 distinct
words after
removing stop
words
Diagram created
in Pajek using the
Kamada-Kawai
layout
(N Patents = 3,935; Word frequency > 598; 50 words connected at the threshold level of cosine ≥ 0.000).
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PATENT ABSTRACTS CO-OCCURRENCE NETWORK
Transformed to
remove lines with
values < .85
Diagram created
in Pajek using the
Kamada-Kawai
layout
(N Patents = 3,935; Word frequency > 598; 50 words connected at the threshold level of cosine ≥ 0.85).
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CONCLUSIONS & FUTURE DIRECTIONS
Conclusions
• RFID is used in many different fields
• United States is the leader in this field
• Identified invisible college of scholars among inventors
Future Work
• Very hot field with high activity
• Update this type of research annually
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REFERENCES
Yen-Chun Wu and Tzu-Chin Yen, “RFID technology innovations: the use of
patent data.” International Journal of Manufacturing Technology and
Management Vol. 10 No. 1 (2007): 106-120
H Dou, V Leveille, S Manullang, and JM Dou Jr., “Patent analysis for
competitive technical intelligence and innovative thinking.” Data Science
JournalVol. 4 (2005): 209-236
Chen-Yuan Liu, James ChingyuYang, "Decoding Patent Information Using
Patent Maps." Data Science JournalVol. 7 (2008): 14-22
Leydesdorff, Loet, “The University-Industry Knowledge Relationship:
Analyzing Patents and the Science Base of Technologies.” Journal of the
American Society for Information Science and TechnologyVol. 55 No. 11
(2004): 991-1001
Leydesdorff, Loet, and Lina Hellsten, “Metaphors and Diaphors in Science
Communication: Mapping the Case of Stem-Cell Research.” Science
CommunicationVol. 27 No. 1 (2005): 64-99
48
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REFERENCES
Websites:
http://en.wikipedia.org/wiki/RFID
http://www.idtechex.com/products/en/view.asp?productcategoryid=93
http://users.fmg.uva.nl/lleydesdorff/software/fulltext/
http://users.fmg.uva.nl/lleydesdorff/indicators/lesson1.htm
http://users.fmg.uva.nl/lleydesdorff/indicators/lesson2.htm
http://users.fmg.uva.nl/lleydesdorff/indicators/lesson5.htm
49