km rfid presentation

RFID PATENT ANALYSIS

KNOWLEDGE MANAGEMENT PROJECT

Shilpa Govada | Shirish Kandekar | Rachana Pejaver | John Wahlman

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

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

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

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

5

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

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

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

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

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

10

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

BASIC STATISTICS

12

3,935 RFID patents were submitted by:

• 1,209 assignees

• 5,843 inventors

• 2,391 primary inventors

• 32 countries

US is dominant

with 78.3% of all

RFID patents

issued in last

decade

13

TOP 20 COUNTRIES BY PATENTS ISSUED

US dominance has

accelerated in

recent years

Zoom in on all

countries except

US

14


Excluding the US,

Japan is the leader

with nearly three

times as many

patents as

Germany

15


North America

leads

Asia overtook

Europe in 2007

16

PATENTS ISSUED BY CONTINENT

Micron

Technology Inc is

leading followed

by IBM

Corporation and

Symbol

Technolgies

17

PATENTS ISSUED BY ASSIGNEE

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

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

19

Communications,

Electrical has lead

significantly since

1997, but

Registers has

grown rapidly

since 2002

20

PATENTS ISSUED BY TECHNOLOGY FIELD

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???

21

PATENTS MOST CITED

Patent 5649296 is the most cited RFID patent, yet its

inventor and assignee are not among the top 20

22

Findings:

Patent Importance and Strength

Average number of cites by country

Average number of cites by assignee

Average number of cites by technology fields

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

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

25

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

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

27

Findings:

Knowledge Diffusion

Country citation network analysis

Institution citation network analysis

Technology citation network analysis

All 32 countries

citing all other

countries

Nodes sized

proportionally to

citation count

Diagram created

in NetDraw

29

COUNTRY CITATION NETWORK ANALYSIS


All 32 countries citing all other countries

Diagram created in GraphViz

30


Showing only links

of 10 or greater

20 countries

Nodes sized

proportionally to

citation count

Diagram created

in NetDraw

31


Showing only links of 10 or greater


32

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

33

INSTITUTION CITATION NETWORK ANALYSIS

Institutions with

links of 15 or

greater

Diagram created

in GraphViz

Micron

IBM

34

TECHNOLOGY FIELD CITATION NETWORK ANALYSIS

Technology Fields

with links of 15 or

greater

Nodes sized

proportionally to

citation count

Diagram created

in NetDraw

35

TECHNOLOGY FIELD CITATION NETWORK ANALYSIS

Technology Fields with links of 15 or greater


36

Findings:

Co-Author Analysis

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

38

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

39

CO-AUTHOR ANALYSIS

Same as previous; diagram created in GraphViz

40

Findings:

Co-Occurrence Analysis

Analysis Procedure

Patent Titles

Patent Abstracts

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

42

Procedure from Loet Leydesdorff of the University of Amsterdam: http://users.fmg.uva.nl/lleydesdorff/software/fulltext/

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).

43

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).

44

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


45

PATENT ABSTRACTS CO-OCCURRENCE NETWORK

Transformed to

remove lines with

values < .85

Diagram created

in Pajek using the

Kamada-Kawai

layout


46

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

47

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

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



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