METHOD AND SYSTEM FOR RATING PATENTS AND OTHER INTANGIBLE ASSETS

• US 20110289096A1
• Filed: 04/22/2011
• Published: 11/24/2011
• Est. Priority Date: 09/14/1999
• Status: Active Grant

• Current Assignee: PatentRatings, LLC
• Original Assignee: PatentRatings, LLC
• Inventors: Barney, Jonathan A.
• Granted Patent: US 9,177,349 B2
• Time in Patent Office: Days
• US Class Current: 707/749
• 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

1-38. -38. (canceled)

39. A method for estimating the probability of a future event occurring relative to a particular identified intellectual property asset of interest, comprising:

storing a first series of data comprising selected metrics identifying and/or quantifying certain selected characteristics of a first population of intellectual property assets for which the event has occurred;

storing a second series of data comprising selected metrics identifying and/or quantifying said selected characteristics of a second population of intellectual property assets for which the event has not occurred or for which it is undetermined whether the event has occurred;

constructing a predictive computer model or algorithm based on said stored first and second series of data, said algorithm being operable to retrieve said first and second series of stored data and to perform certain mathematical or statistical calculations thereon to generate an output score or estimated probability that is generally predictive of the event having either occurred or not occurred relative to each intellectual property asset in said first or second populations of intellectual property assets; and

providing as input to said algorithm a third series of data comprising selected metrics identifying and/or quantifying certain selected characteristics of said particular identified intellectual property asset of interest and operating said computer model or algorithm independently of said stored first and second series of data to directly calculate an estimated probability of the event occurring in the future relative to said identified intellectual property asset of interest.

40. The method of claim 39 wherein said first and/or second populations of intellectual property assets comprise patents that have been the subject of prior litigation through final judgement and wherein said event 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.

41. The method of claim 39 wherein said first and/or second populations of intellectual property assets comprise selected samples of issued U.S. patents and wherein said event comprises one or more of the following:

payment of the first scheduled maintenance fee, payment of the second scheduled maintenance fee, payment of the third scheduled maintenance fee.

42. The method of claim 39 wherein said first and second populations of intellectual property assets have roughly the same population size.

43. The method of claim 42 wherein said first and second populations of intellectual property assets have a population size of greater than about 1000.

44. The method of claim 43 wherein said first and second populations of intellectual property assets have a population size of between about 20,000 and 80,000.

45. The method of claim 39 wherein said selected metrics comprise one or more characteristics of each said intellectual property asset in said first and second populations of intellectual property assets that are determined or assumed to have either a positive or negative correlation with the occurrence or non-occurrence of said event.

46. The method of claim 39 wherein said algorithm comprises a multiple regression model that correlates multiple individual predictor variables comprising said selected metrics to a single desired criterion variable comprising the approximated probability of said event either occurring or not occurring.

47. The method of claim 46 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.

48. The method of claim 47 wherein said regression includes between about 15 and 25 predictor variables.

49. The method of claim 48 comprising the further step of determining the statistical accuracy of the regression model in accordance with the general formula:

SA(m)=CO/(CO+IN)

where;

SA(m)=statistical accuracy of regression model (m)

CO=number of correct predictions for model (m)

IN=number of incorrect predictions for model (m).

50. The method of claim 49 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).

51. The method of claim 39 comprising the further step of generating an event probability report for said identified selected intellectual property asset of interest, said report including basic information identifying said selected intellectual property asset of interest and said estimated probability of said event occurring or not occurring within a predetermined period of time in the future.

52. An event probability report generated according to the method of claim 39.

53. The method of claim 39 comprising the further steps of:

providing data representative of an intellectual property asset value distribution curve, the shape of the curve generally representing an approximated distribution of patent value according to an estimated probability of said event either occurring or not occurring; and

using said representative data to estimate a value or value range for said selected intellectual property asset of interest according to the estimated probability of said event either occurring or not occurring relative to said selected intellectual property asset of interest.

54-74. -74. (canceled)