Method and system for rating patents and other intangible assets

• US 6,556,992 B1
• Filed: 09/14/2000
• Issued: 04/29/2003
• Est. Priority Date: 09/14/1999
• Status: Expired due to Term

• Current Assignee: PatentRatings, LLC
• Original Assignee: PatentRatings, LLC
• Inventors: Barney, James R., Barney, Jonathan A.
• Primary Examiner(s): Shah, Sanjiv
• Application Number:
  US09/661,765
• Time in Patent Office: 957 Days
• Field of Search: 707/6, 707/1, 707/2, 707/3, 707/4, 707/5, 707/7, 707/10, 707/101, 707/102, 707/104, 706/45
• US Class Current: 1/1
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 50/184 Intellectual property management
• CPC Class Codes: G06Q 99/00 Subject matter not provided for in other groups of this subclass
• CPC Class Codes: Y10S 707/93 intellectual property analysis
• CPC Class Codes: Y10S 707/99936 Pattern matching access
• CPC Class Codes: Y10S 707/99937 Sorting

Abstract

A statistical patent rating method and system is provided for independently assessing the relative breadth (“B”), defensibility (“D”) and commercial relevance (“R”) of individual patent assets and other intangible intellectual property assets. The invention provides new and valuable information that can be used by patent valuation experts, investment advisors, economists and others to help guide future patent investment decisions, licensing programs, patent appraisals, tax valuations, transfer pricing, economic forecasting and planning, and even mediation and/or settlement of patent litigation lawsuits. In one embodiment the invention provides a statistically-based patent rating method and system whereby relative ratings or rankings are generated using a database of patent information by identifying and comparing various characteristics of each individual patent to a statistically determined distribution of the same characteristics within a given patent population. For example, a first population of patents having a known relatively high intrinsic value or quality (e.g. successfully litigated patents) is compared to a second population of patents having a known relatively low intrinsic value or quality (e.g. unsuccessfully litigated patents). Based on a statistical comparison of the two populations, certain characteristics are identified as being more prevalent or more pronounced in one population group or the other to a statistically significant degree. Multiple such statistical comparisons are used to construct and optimize a computer model or computer algorithm that can then be used to predict and/or provide statistically-accurate probabilities of a desired value or quality being present or a future event occurring, given the identified characteristics of an individual patent or group of patents.

Claims

1. A computer-automated method for rating or ranking patents or other intangible assets comprising:

selecting a first population of patents having a first quality or characteristic;

selecting a second population of patents having a second quality or characteristic that is different from or assumed to be different from said first quality or characteristic;

providing a computer-accessible database of selected patent metrics representative of or describing particular corresponding characteristics of each said patents in said first and second patent populations;

constructing a computer regression model based on said selected patent metrics, said regression model being operable to input said selected patent metrics for each said patent in said first and second patent populations and to output a corresponding rating or ranking that is generally predictive of the presence or absence of said first and/or second quality in said first and second patent populations according to a determined statistical accuracy; and

using said regression model to rate or rank one or more patents in a third patent population by inputting into said regression model selected patent metrics representative of or describing corresponding characteristics of said one or more patents in said third population to be rated or ranked and causing said regression model to output a corresponding rating or ranking based thereon.

2. The method of claim 1 wherein said first population of patents have the quality or characteristic of being the subject of prior litigation and wherein said second population of patents have the quality or characteristic of not having been the subject of prior litigation.

3. The method of claim 1 wherein said first population of patents have the quality or characteristic of being successfully litigated and wherein said second population of patents have the quality or characteristic of being unsuccessfully litigated.

4. The method of claim 1 wherein said first population of patents have the quality or characteristic of being found infringed in prior litigation and wherein said second population of patents comprises a random sample of patents from the general patent population of issued patents.

5. The method of claim 1 wherein said first population of patents have the quality or characteristic of being maintained in force for more than a predetermined period of years and wherein said second population of patents have the quality or characteristic of being abandoned within said predetermined period of years.

6. The method of claim 1 wherein said first and second patent populations have roughly the same population size.

7. The method of claim 6 wherein said first and second patent populations have a population size of greater than about 1000 patents.

8. The method of claim 7 wherein said first or second patent populations have a population size of between about 20,000 and 80,000 patents.

9. The method of claim 1 wherein said third population of patents is the same as and/or overlaps either said first or second populations of patents.

10. The method of claim 1 wherein said third population of patents comprises essentially all newly issued patents as periodically published by the PTO.

11. The method of claim 1 wherein said third population of patents is selected from the group consisting of either:

an individual selected patent, a group of commonly owned patents, a portfolio of patents controlled by one or more public corporations, a portfolio of patents controlled by one or more pre-IPO companies, all patents listing one or more particular named inventors, all patents naming one or more particular prosecuting attorneys or law firms, all patents classified within one or more PTO patent classifications, or all patents issued between a first date and a second date.

12. The method of claim 1 wherein said selected patent metrics comprise one or more characteristics of each said patents in said first and second patent populations that are determined or assumed to have either a positive or negative correlation with the presence or absence of said first or second quality to a statistically significant degree.

13. The method of claim 12 wherein said selected patent metrics include one or more of the following:

number of claims per patent, number of words per claim, different words per claim, length of patent specification, number of drawing pages or figures, number of cited prior art references, age of cited references, number of subsequent citations received, subject matter classification and sub-classification, origin of the patent, payment of maintenance fees, name of prosecuting attorney or law firm, examination art group, or length of pendency in the PTO.

14. The method of claim 12 wherein at least one of said patent metrics include one or more of the following:

patent marking data, claim relatedness, patent relatedness, or claim type.

15. The method of claim 12 wherein at least one of said patent metrics comprises a modified claim word-count metric whereby each word and/or word phrase in a patent claim of interest is assigned a certain point value generally proportional to its determined frequency of use in a relevant patent population and wherein the word-count metric is set equal to the sum of each of the individual word point values for essentially all of the words or word phrases contained within said claim.

16. The method of claim 12 wherein at least one of said selected patent metrics comprises a relatedness metric generally indicative of the commonality of word or word phrase usage between one or more patent claims and/or patent specifications.

17. The method of claim 1 wherein said regression model comprises a multiple regression model that correlates multiple individual predictor variables comprising said selected patent metrics to a single desired criterion variable comprising the desired output rating or ranking.

18. The method of claim 17 wherein said multiple regression model has the form:

19. The method of claim 18 wherein said regression model includes no more than about 10 to 30 predictor variables.

20. The method of claim 19 wherein said regression model includes between about 15 and 25 predictor variables.

21. The method of claim 1 wherein said rating or ranking is generally predictive of the probability of the patents in the third population being found either valid or invalid, being found either infringed or not infringed, or being maintained in force beyond a predetermined time period.

22. The method of claim 1 comprising the further step of determining the statistical accuracy of the regression model in accordance with the general formula:

23. The method of claim 22 comprising the further steps of:

incrementally modifying the regression model (m) to produce a modified regression model (m+1);

determining the statistical accuracy of the modified regression model (m+1);

comparing the statistical accuracy of the modified regression model (m+1) to the previously determined statistical accuracy of regression model (m); and

either repeating said incremental modification of the regression model (m+1) to produce a further modified regression model (m+2) if the determined statistical accuracy of the modified regression model (m+1) is greater than the determined statistical accuracy of the regression model (m), or reversing said incremental modification of regression model (m+1) to produce the original regression model (m) if the determined statistical accuracy of the modified regression model (m+1) is less than the determined statistical accuracy of the regression model (m).

24. The method of claim 1 comprising the further step of generating a patent rating report for an individual selected patent or selected group of patents contained in said third population of patents, said report including basic information identifying said selected patent or selected group of patents and one or more of said ratings or rankings determined therefor.

25. The method of claim 24 wherein said patent rating report is generated in response to an electronic request transmitted over a computer network and wherein said report is generated and displayed automatically without further human intervention.

26. The method of claim 24 comprising the further step of, after generating said report, automatically without further human intervention transmitting said report electronically over a computer network to one or more intended recipients.

27. The method of claim 24 wherein said patent rating report contains at least one reported rating or ranking that is generally representative of the breadth (“

B”

) or likely infringement of the selected patent or group of patents, at least one reported rating or ranking that is generally representative of the defensibility (“

D”

) or likely validity of the selected patent or group of patents, and at least one reported rating or ranking that is generally representative of the commercial relevance (“

R”

) or technical merit of the selected patent or group of patents.

28. The method of claim 27 wherein said B and D ratings or rankings are calculated by one or more computer regression models constructed and adjusted to be predictive of known litigation outcomes of selected first and second populations of litigated patents based on said selected patent metrics, and wherein said R rating or ranking is generated by a computer regression model constructed and adjusted to be generally predictive of known patent maintenance or mortality rates of selected first and second populations of maintained or abandoned patents based on said selected patent metrics.

29. A patent rating report generated according to the method of claim 24.

30. A patent rating report generated in accordance with the method of claim 24 and wherein said report contains an organized list of said patent ratings or rankings for substantially every issued patent within a predefined patent population.

31. A patent rating report generated in accordance with the method of claim 30, and including the further step of determining and reporting the statistical accuracy of substantially each said patent rating or ranking contained in said report.

32. The method of claim 1 comprising the further steps of:

providing data representative of a patent value distribution curve, the shape of the curve generally representing an estimated distribution of patent value according to relative ratings or rankings within said third patent population and wherein the area under the curve is generally proportional to the total estimated value of all patents in said third patent population; and

using said representative data to estimate a value or value range for an individual selected patent from said third patent population according to its relative rating or ranking within said third patent population.

33. A high-speed method for automatically scoring or rating a predefined population of selected patents in a sequential series of newly issued patents published periodically by the PTO and for determining and storing certain rating or scoring information specific to each said selected patent in said sequential series, said method comprising:

obtaining a substantial full-text copy of the specification and claims of each said selected patent in the sequential series in a computer text file format or other computer-accessible format;

using a computer program to automatically access and read each said computer text file and to extract therefrom certain selected patent metrics representative of or describing particular corresponding characteristics of each said selected patent in the sequential series;

inputting said extracted patent metrics into a computer regression algorithm, said algorithm being selected and adjusted to produce in response to said patent metrics a corresponding rating output or mathematical score that is generally predictive of a particular patent quality of interest and/or the probability of a particular future event occurring; and

for each said selected patent in the sequential series storing the resulting algorithm output in a computer accessible storage device in association with other selected information identifying said selected patent.

34. The method of claim 33 wherein said predefined population of patents comprises one or more of the following:

a group of commonly owned patents, a portfolio of patents controlled by one or more public corporations, a portfolio of patents controlled by one or more pre-IPO companies, all patents listing one or more particular named inventors, all patents naming one or more particular prosecuting attorneys or law firms, all patents classified within one or more PTO patent classifications, or all patents issued between a first date and a second date.

35. The method of claim 33 wherein said extracted patent metrics comprise one or more characteristics of each said patents in said predefined population of patents that are determined or assumed to have either a positive or negative correlation with the presence or absence of the particular quality of interest and/or the probability of a particular future event occurring relative to each said patent in the predetermined patent population.

36. The method of claim 35 wherein said extracted patent metrics include one or more of the following:

number of claims per patent, number of words per claim, different words per claim, length of patent specification, number of drawing pages or figures, number of cited prior art references, age of cited references, number of subsequent citations received, subject matter classification and sub-classification, origin of the patent, payment of maintenance fees, name of prosecuting attorney or law firm, examination art group, or length of pendency in the PTO.

37. The method of claim 35 wherein at least one of said extracted patent metrics include one or more of the following:

patent marking data, claim relatedness, patent relatedness, or claim type.

38. The method of claim 35 wherein at least one of said extracted patent metrics comprises a modified claim word-count metric whereby each word and/or word phrase in a patent claim of interest is assigned a certain point value generally proportional to its determined frequency of use in a relevant patent population and wherein the word-count metric is set equal to the sum of each of the individual word point values for essentially all of the words or word phrases contained within said claim.

39. The method of claim 35 wherein at least one of said selected patent metrics comprises a relatedness metric generally indicative of the commonality of word or word phrase usage between one or more patent claims and/or patent specifications.

40. The method of claim 33 wherein said regression model comprises a multiple regression model that correlates multiple individual predictor variables comprising said extracted patent metrics to a single desired criterion variable comprising the algorithm output.

41. The method of claim 40 wherein said multiple regression model has the form:

 

CV_m=ƒ

{PV₁, PV₂ . . . PV_n}

where;

CV_m=criterion variable or quality/event desired to be predicted

PV_n=predictor variables or selected patent metrics.

42. The method of claim 41 wherein said regression model includes no more than about 10 to 30 predictor variables.

43. The method of claim 42 wherein said regression model includes between about 15 and 25 predictor variables.

44. The method of claim 33 comprising the further step of determining the statistical accuracy of the regression model in accordance with the general formula:

45. The method of claim 33 comprising the further step of generating a patent rating report for each said selected patent contained within said predefined population of patents, said report including basic information identifying each said selected patent and the corresponding algorithm output determined therefor.

46. A patent rating report generated according to the method of claim 45.

47. A patent rating report generated in accordance with the method of claim 45 and including the further step of determining and reporting in said rating report the statistical accuracy of said algorithm output.

48. The method of claim 33 comprising the further steps of:

providing data representative of a patent value distribution curve, the shape of the curve generally representing an estimated distribution of patent value according to relative ratings or rankings within said predefined patent population and wherein the area under the curve is generally proportional to the total estimated value of all patents in said predefined patent population; and

using said representative data to estimate a value or value range for an individual selected patent from said predefined patent population according to its relative rating or ranking within said predefined patent population.

49. An automated method for determining an estimated rating or ranking of an intellectual property asset to be rated, comprising:

storing first objectively determinable characteristics of representative intellectual property assets and at least one objectively determinable quality corresponding to each of the representative intellectual property assets;

constructing a computer regression model based on the first objectively determinable characteristics and the at least one objectively determinable quality corresponding to each of the representative intellectual property assets, said regression model being selected and adjusted to input said first objectively determinable characteristics corresponding to each of the representative intellectual property assets and to output in each case a corresponding mathematical rating or ranking that is generally predictive, according to a determined statistical accuracy, of said at least one objectively determinable quality corresponding to each of the representative intellectual property assets;

analyzing the intellectual property asset to be rated to determine second objectively determinable characteristics of the intellectual property asset to be rated; and

using said regression model to rate or rank said intellectual property asset to be rated by inputting said second objectively determinable characteristics into said regression model and causing said regression model to output a corresponding estimated rating or ranking.

50. The method of claim 49 wherein said representative intellectual property assets comprise patents that have been the subject of prior litigation through final judgement and wherein said at least one objectively determinable quality comprises one or more of the following:

a final judgement of infringement, a final judgement of non-infringement, a final judgement of invalidity, a final judgement of non-invalidity, a final judgement in favor of the patentee, a final judgement in favor of the accused.

51. The method of claim 49 wherein said representative intellectual property assets comprise patents maintained in force for more than a predetermined period of years.

52. The method of claim 49 wherein said intellectual property to be rated comprises one or more of the following:

an individual selected patent, a group of commonly owned patents, a portfolio of patents controlled by one or more public corporations, a portfolio of patents controlled by one or more pre-IPO companies, all patents listing one or more particular named inventors, all patents naming one or more particular prosecuting attorneys or law firms, all patents classified within one or more PTO patent classifications, or all patents issued between a first date and a second date.

53. The method of claim 49 wherein said first and second objectively determinable characteristics comprise one or more characteristics of said representative intellectual property assets that are determined or assumed to have either a positive or negative correlation with the presence or absence of said objectively determinable quality.

54. The method of claim 49 wherein said intellectual property asset to be rated comprises one or more patents and wherein first and second objectively determinable characteristics comprise one or more of the following:

number of claims per patent, number of words per claim, different words per claim, length of patent specification, number of drawing pages or figures, number of cited prior art references, age of cited references, number of subsequent citations received, subject matter classification and sub-classification, origin of the patent, payment of maintenance fees, name of prosecuting attorney or law firm, examination art group, or length of pendency in the PTO.

55. The method of claim 54 wherein at least one of said first and second objectively determinable characteristics include one or more of the following:

patent marking data, claim relatedness, patent relatedness, or claim type.

56. The method of claim 54 wherein at least one of said first and second objectively determinable characteristics comprises a modified claim word-count metric whereby each word and/or word phrase in a patent claim of interest is assigned a certain point value generally proportional to its determined frequency of use in a relevant patent population and wherein the word-count metric is set equal to the sum of each of the individual word point values for essentially all of the words or word phrases contained within said claim.

57. The method of claim 54 wherein at least one of said first and second objectively determinable characteristics comprises a relatedness metric generally indicative of the commonality of word or word phrase usage between one or more patent claims and/or patent specifications.

58. The method of claim 49 wherein said regression model comprises a multiple regression model that correlates multiple individual predictor variables comprising said first and second objectively determinable characteristics to a single desired criterion variable comprising said objectively determinable quality.

59. The method of claim 58 wherein said multiple regression model has the form:

60. The method of claim 59 wherein said regression model includes between about 15 and 25 predictor variables.

61. The method of claim 49 wherein said rating or ranking is generally predictive according to a determined statistical accuracy of the probability of a future event affecting said intellectual property asset to be rated.

62. The method of claim 61 comprising the further step of determining the statistical accuracy of the regression model in accordance with the general formula:

63. The method of claim 62 comprising the further steps of:

incrementally modifying the regression model (m) to produce a modified regression model (m+1);

determining the statistical accuracy of the modified regression model (m+1);

comparing the statistical accuracy of the modified regression model (m+1) to the previously determined statistical accuracy of regression model (m); and

either repeating said incremental modification of the regression model (m+1) to produce a further modified regression model (m+2) if the determined statistical accuracy of the modified regression model (m+1) is greater than the determined statistical accuracy of the regression model (m), or reversing said incremental modification of regression model (m+1) to produce the original regression model (m) if the determined statistical accuracy of the modified regression model (m+1) is less than the determined statistical accuracy of the regression model (m).

64. The method of claim 49 comprising the further step of generating a rating report containing at least one reported rating or ranking that is generally representative of the breadth (“

B”

) of the intellectual property asset to be rated, at least one reported rating or ranking that is generally representative of the defensibility (“

D”

) of the intellectual property asset to be rated, and at least one reported rating or ranking that is generally representative of the commercial relevance (“

R”

) of the intellectual property asset to be rated.

65. A rating report generated according to the method of claim 64.

66. The method of claim 49 comprising the further steps of:

providing data representative of an intellectual property asset value distribution curve, the shape of the curve generally representing an estimated distribution of patent value according to relative ratings or rankings of said representative intellectual property assets and wherein the area under the curve is generally proportional to the total estimated value of all representative intellectual property assets; and

using said representative data to estimate a value or value range for said intellectual property asset to be rated according to its relative rating or ranking among said representative intellectual property assets.