Patentee Name Harmonisation - ecoom.be

More documents

Recommendations

Info

Acknowledgements This publication has been managed by Eurostat, Unit F4 — Education, Science and Culture Statistics — headed by Jean-Louis Mercy. Project leader Bernard Félix — bernard.felix@cec.eu.int Eurostat, Unit F4 — Education, Science and Culture Statistics Statistical Office of the European Communities, Joseph Bech Building, Alphonse Weicker, 5 L-2721, Luxembourg. Authors Tom Magerman, Bart Van Looy, Xiaoyan Song Production The working paper was prepared by Tom Magerman 2, 3 , Bart Van Looy 1, 2, 3 and Xiaoyan Song 3 . When quoting this report, please use the following reference: Magerman, T., Van Looy, B. & Song, X. (2006) Data Production Methods for Harmonized Patent Indicators: Patentee Name Harmonization. EUROSTAT Working Paper and Studies, Luxemburg. 1 Managerial Economics, Strategy and Innovation, Faculty of Economics & Applied Economics, K.U.Leuven 2 Research Division INCENTIM, Faculty of Economics & Applied Economics, K.U.Leuven 3 Steunpunt O&O Statistieken
Table of contents 1 Introduction................................................................................................................................. 1 2 Patentee name harmonization and legal entity harmonization .................................................. 2 3 Existing name-harmonization approaches ................................................................................. 3 3.1 USPTO CONAME assignee name harmonization................................................................. 3 3.2 DERWENT WPI company name harmonization.................................................................... 4 4 A content-driven name harmonization approach focusing on accuracy .................................... 5 4.1 Data pre-processing............................................................................................................... 6 4.2 Name cleaning ....................................................................................................................... 7 5 Results and Impact..................................................................................................................... 8 6 Directions for further development ........................................................................................... 10 6.1 Approximate string searching............................................................................................... 10 6.2 Automatic acronym generation ............................................................................................ 13 6.3 Introducing address information (in conjunction with name similarity) ................................ 15 7 CONCLUSION.......................................................................................................................... 16 8 References ............................................................................................................................... 17 APPENDIX 1: STEP-BY-STEP METHODOLOGY AND APPLICATION USING EPO AND USPTO PATENTEE NAMES.............................................................................................................................. 18 1 Data pre-processing ................................................................................................................. 18 1.1 Character cleaning ............................................................................................................... 18 1.2 Punctuation cleaning (pre-parsing) ...................................................................................... 22 2 Name cleaning.......................................................................................................................... 28 2.1 Legal form indication treatment............................................................................................ 28 2.2 Common company word removal ........................................................................................ 35 2.3 Spelling variation harmonization .......................................................................................... 37 2.4 Condensing .......................................................................................................................... 38 2.5 Umlaut harmonization .......................................................................................................... 39 2.6 Cleaned name...................................................................................................................... 40 3 Harmonization results............................................................................................................... 42 3.1 Original names matched to harmonized names .................................................................. 42 3.2 Additional patents assigned to harmonized names ............................................................. 44 3.3 Patent distribution amongst patentees................................................................................. 46 3.4 Patent ranking of patentees ................................................................................................. 47 APPENDIX 2: ALL SEARCH AND REPLACE STATEMENTS FOR ALL LEGAL FORMS TO BE REMOVED AT THE END OF A NAME ................................................................................................. 51 APPENDIX 3: TOP 200 OCCURRING LAST WORDS......................................................................... 69 APPENDIX 4: TOP 200 OCCURRING FIRST WORDS ....................................................................... 71 APPENDIX 5: TOP 200 PATENTEES BEFORE NAME CLEANING AND HARMONIZATION ........... 73 APPENDIX 6: TOP 200 PATENTEES AFTER NAMe CLEANING AND HARMONIZATION............... 77 APPENDIX 7: VALIDATION EXERCICE ON 35 HARMONIZED NAMES............................................ 81
Page 1: Data Production Methods for Harmoni
Page 5 and 6: 2 PATENTEE NAME HARMONIZATION AND L
Page 7 and 8: 3.2 DERWENT WPI company name harmon
Page 9 and 10: Figure 1: Overview schema name clea
Page 11 and 12: 4.2.3 Spelling variation harmonizat
Page 13 and 14: 6 DIRECTIONS FOR FURTHER DEVELOPMEN
Page 15 and 16: A considerable number of name varia
Page 17 and 18: IBM INTERNATION BUSINESS MACHINES I
Page 19 and 20: DIAGNOSTICS MITSUBISHIJUKOGYO MITSU
Page 21 and 22: APPENDIX 1: STEP-BY-STEP METHODOLOG
Page 23 and 24: 1.1.3 Replace propriety coded chara
Page 25 and 26: 220 "Ü" "U" 221 "Ý" "Y" 159 "Ÿ"
Page 27 and 28: Impact From 438,069 unique names to
Page 29 and 30: “%,GMBH.%” “, GMBH.” “%,G
Page 31 and 32: 2 NAME CLEANING 2.1 Legal form indi
Page 33 and 34: INCORPORATED Incorporated AS Akties
Page 35 and 36: Some legal form indications are not
Page 37 and 38: " GMBH & CO. KG " 191 GMBH Replace
Page 39 and 40: "AND COMPANY" 120 "& COMPANY" 10,90
Page 41 and 42: "TECHNOLOGIES" 7,587 "TECHNOLOGY" "
Page 43 and 44: marked in the previous step as a na
Page 45 and 46: 3 HARMONIZATION RESULTS As the fina
Page 47 and 48: 13 37 12 35 11 61 10 82 9 136 8 179
Page 49 and 50: 3.3 Patent distribution amongst pat
Page 51 and 52: product). Appendix 5 contains the t
Page 53 and 54:
The absolute differences in the num
Page 55 and 56:
1056 ", IN.C" 4 INCORPORATED Remove
Page 57 and 58:
1199 " MFG., LTD." 23 LIMITED Repla
Page 59 and 60:
1314 " (I.P) LIMITED" 1 LIMITED Rem
Page 61 and 62:
1450 " P.L.C." 60 PLC Remove 1451 "
Page 63 and 64:
1585 " A.S." 240 AS Remove 1586 " A
Page 65 and 66:
1715 CO." " GESELLSCHAFT M.B.H & CO
Page 67 and 68:
1844 " AKTIENGESELLSCHAFT & CO. KG"
Page 69 and 70:
1981 " MBH." 19 GMBH Remove 1982 "
Page 71 and 72:
2053 " KOGYOLKABUSHIKI KAISHA" 1 20
Page 73 and 74:
LAST WORD NBR OF CUM % LAST WORD NB
Page 75 and 76:
FIRST WORD NBR OF CUM % FIRST WORD
Page 77 and 78:
52 NIKON CORPORATION 4,500 615,317
Page 79 and 80:
177 UNISYS CORPORATION 1,653 942,72
Page 81 and 82:
54 HENKEL KOMMANDITGESELLSCHAFT AUF
Page 83 and 84:
177 CASIO COMPUTER COMPANY 1,848 1,
Page 85:
DIMPLEX NORTH AMERICA 1 22 1 22 0 0
show all

Patentee Name Harmonisation - ecoom.be

Create successful ePaper yourself

Delete template?

Save as template?