Information processing apparatus, information processing method, and program

Abstract

To grasp concentration and selected technology classification for each applicant.SOLUTION: The information processing device 10 includes an acquisition unit 20 that acquires predetermined acquired information 220 from the intellectual property data 5, a calculation unit 30 that calculates an intellectual property evaluation value 310 in a predetermined period for each technology classification for each applicant based on the acquired information 220, a distribution creation unit 40 that creates a distribution based on the intellectual property evaluation value 310 calculated by the calculation unit 30, and a distribution placement unit 50 that places the distribution.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Techniques for analyzing information on companies or individuals who are patent applicants or patent holders using patent information are known (see, for example, Patent Document 1, Patent Document 2, and Non-Patent Document 1). Patent Document 1 discloses a patent profit calculation device characterized by calculating the correlation with business revenue values ​​for each patent holder. Patent Document 2 discloses a technique for associating patent holders with technical features based on a data set correlating patent classification information with patent holders, treating each patent holder as a node and the association between each patent holder as an edge, and clustering each node into groups with relatively high relevance based on the state of connection of each node through the edges, thereby creating a graph-style technology overview diagram. Non-Patent Document 1 discloses a technique for correcting patent evaluation values. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2011-138331 [Patent Document 2] Japanese Patent Publication No. 2022-158621 [Non-patent literature]

[0004] [Non-Patent Document 1] Ernst H, Omland N. The Patent Asset Index - A new approach to benchmark patent portfolios. World Patent Informat (2010), doi:10.1016 / j.wpi.2010.08.008 Summary of the Invention [Problem to be solved by the invention]

[0005] In the information processing device, information processing method and program, it is preferable to grasp the technology classification characterized by the concentration and selection of each applicant.

[0006] The present invention has been made in view of the above-mentioned circumstances, and has as its object to provide an information processing device and an information processing method that are capable of grasping the concentration of each applicant and the selected technology classification. [Means for solving the problem]

[0007] In order to achieve the above object, an information processing device of a first aspect of the present invention includes an acquisition unit that acquires predetermined acquired information from intellectual property data, a calculation unit that calculates an intellectual property evaluation value for each applicant for each technology classification for a predetermined period based on the acquired information, a distribution generation unit that generates a distribution based on the intellectual property evaluation value calculated by the calculation unit, and a distribution allocation unit that allocates the distribution. Equipped with

[0008] In the information processing device of the first aspect of the present invention, a distribution is generated for each applicant for each technology classification based on the intellectual property evaluation value calculated for a predetermined period based on the acquired information obtained from intellectual property data, and the trend of technology classification for each applicant for the predetermined period is displayed in the distribution. As a result, it is possible to grasp technology classifications characterized by concentration and selection for each applicant.

[0009] In the information processing device of the second aspect of the present invention, in addition to the first aspect, the acquisition unit acquires, as the acquired information, an evaluation value for each applicant for each technology category over a predetermined period.

[0010] In the information processing device of the second aspect of the present invention, the evaluation value of an intellectual property can be easily calculated by acquiring evaluation values ​​for each applicant for each technology category for a predetermined period as acquired information. Therefore, it is easy to grasp technology categories characterized by concentration and selection for each applicant.

[0011] In a third aspect of the information processing device of the present invention, in the second aspect, the evaluation value includes at least one of the number of applications, the number of published applications, the number of patents, the number of citations, the number of times cited, and an aggregate value of weighted values ​​thereof.

[0012] The information processing device of the third aspect of the present invention can generate a distribution based on at least one of the number of applications, number of published applications, number of patents, number of citations, number of cited applications, and a total value of weighted values ​​thereof, thereby enabling accurate understanding of technology classification characterized by concentration and selection for each applicant.

[0013] An information processing device of a fourth aspect of the present invention is any one of the first to third aspects, wherein the calculation unit uses first acquired information from a predetermined period and second acquired information from a period different from the first acquired information based on the acquired information to calculate, as an intellectual property evaluation value, the difference between the evaluation value of the second acquired information based on the first acquired information for each technology classification, and calculates a set of the intellectual property evaluation values ​​as difference information.

[0014] In the information processing device of the fourth aspect of the present invention, a set of intellectual property evaluation values ​​calculated based on the difference between the evaluation value of each technology classification of the second acquired information and the evaluation value of each technology classification of the first acquired information is calculated as differential information, and the differential information is reflected in the distribution. Therefore, it is possible to grasp more accurately the technology classification characterized by the concentration and selection of each applicant.

[0015] An information processing device of a fifth aspect of the present invention is any one of the first to fourth aspects, wherein the distribution generation section generates a normal distribution as the distribution.

[0016] In the information processing device of the fifth aspect of the present invention, a normal distribution is generated as a distribution, and random variables for each technology classification are displayed in the normal distribution. This allows for a more accurate understanding of technology classifications characterized by concentration and selection for each applicant.

[0017] An information processing device of a sixth aspect of the present invention is, in the fourth aspect, the distribution generation unit generates a normal distribution based on the difference information, obtains an expected value and a standard deviation, and stores the normal distribution, the expected value, and the standard deviation.

[0018] In the information processing device of the sixth aspect of the present invention, a normal distribution generated based on expected values, standard deviations, and difference information is stored, and the normal distribution is thereby stored. Therefore, the stored normal distribution is used to visualize the technology classification for each applicant. As a result, it is possible to grasp with greater accuracy the technology classification characterized by the concentration and selection for each applicant.

[0019] In a seventh aspect of the information processing device of the present invention, in the fifth aspect, the distribution arrangement unit arranges the normal distribution on a three-dimensional coordinate axis, with the random variable of the normal distribution as the random variable axis, at least one of the expected value, standard deviation, and an aggregate value of their weighted values ​​as the base axis, and the probability density of the normal distribution as the random density axis.

[0020] In the information processing device of the seventh aspect of the present invention, the normal distribution is arranged on a three-dimensional coordinate axis, with the random variable of the normal distribution as the random variable axis, at least one of the expected value, standard deviation, and a weighted aggregate value of these values ​​as the base axis, and the probability density of the normal distribution as the probability density axis, so that the normal distributions of multiple applicants are arranged along the base axis. This makes it possible to grasp the rate of change in the concentration and selection of multiple applicants.

[0021] An information processing device of an eighth aspect of the present invention is, in the fifth aspect, wherein the distribution arrangement unit arranges the normal distribution on a two-dimensional coordinate axis having a random variable of the normal distribution as a random variable axis and at least one of the expected value, standard deviation, and an aggregate value of their weighted values ​​as a base axis.

[0022] In the information processing device of the eighth aspect of the present invention, the normal distribution is visualized two-dimensionally by plotting the normal distribution on two-dimensional coordinate axes, with the random variable of the normal distribution as the random variable axis and at least one of the expected value, standard deviation, and the aggregated value of their weighted values ​​as the base axis. This makes it possible to further grasp the rate of change in the concentration and selection of multiple applicants, and to accurately grasp the concentration and selected technology classification for each applicant.

[0023] An information processing device of a ninth aspect of the present invention is, in the fifth aspect, wherein the distribution arrangement unit arranges the normal distribution on a three-dimensional coordinate axis having a random variable of the normal distribution as a random variable axis, a probability density of the normal distribution as a random density axis, and a time axis.

[0024] In the information processing device of the ninth aspect of the present invention, the normal distribution is arranged on three-dimensional coordinate axes, with the random variable of the normal distribution on the random variable axis, the probability density of the normal distribution on the probability density axis, and the time axis, so that the normal distributions of the applicant over a predetermined period are arranged along the time axis, thereby making it possible to grasp the tendency of the applicant's technology classification.

[0025] An information processing device of a tenth aspect of the present invention is based on the fifth aspect, wherein the distribution arrangement unit arranges the normal distribution on a two-dimensional coordinate axis having a random variable axis representing the random variable of the normal distribution and a time axis.

[0026] In the information processing device of the tenth aspect of the present invention, the normal distribution is plotted on a two-dimensional coordinate axis with the random variable of the normal distribution as the random variable axis and the time axis as the time axis, thereby visualizing the normal distribution of the applicant over a predetermined period in two dimensions, thereby making it possible to grasp the transition of each applicant's technology classification.

[0027] An information processing method of an eleventh aspect of the present invention acquires specified acquired information from intellectual property data, calculates an intellectual property evaluation value for each applicant for each technology classification for a specified period based on the acquired information, and generates a distribution based on the intellectual property evaluation values.

[0028] In the information processing method of the eleventh aspect of the present invention, a distribution is generated based on the intellectual property evaluation value calculated for a predetermined period for each technology classification for each applicant based on the acquired information obtained from intellectual property data, and the trend of technology classification for each applicant for a predetermined period is displayed in the distribution. As a result, it is possible to grasp the concentration of each applicant and the selected technology classification.

[0029] A program according to a twelfth aspect of the present invention causes a computer to execute a process of acquiring predetermined acquired information from intellectual property data, calculating an intellectual property evaluation value for each applicant for each technology classification for a predetermined period based on the acquired information, and generating a distribution based on the intellectual property evaluation values.

[0030] The program of the twelfth aspect of the present invention generates a distribution based on the intellectual property evaluation value calculated for a predetermined period for each technology classification for each applicant based on the acquired information obtained from intellectual property data, thereby displaying the trend of technology classification for each applicant for a predetermined period in the distribution. As a result, it is possible to grasp the concentration of each applicant and the selected technology classification. [Effects of the Invention]

[0031] The information processing device, information processing method, and program according to the present invention make it possible to grasp technology classifications characterized by concentration and selection for each applicant. [Brief explanation of the drawings]

[0032] [Figure 1] 1 is a schematic diagram illustrating a hardware configuration of an information processing device according to a first embodiment. [Figure 2] FIG. 1 is a diagram illustrating a functional configuration of an information processing device according to a first embodiment. [Figure 3] FIG. 2 is an explanatory diagram illustrating an acquisition unit according to the first embodiment. [Figure 4] FIG. 2 is an explanatory diagram illustrating a calculation unit according to the first embodiment. [Figure 5] FIG. 3 is an explanatory diagram illustrating a distribution generation unit according to the first embodiment. [Figure 6]4A and 4B are diagrams illustrating an example of arrangement by a distribution arrangement unit according to the first embodiment. [Figure 7] 4 is a flowchart showing a flow of processing by the information processing device according to the first embodiment. [Figure 8] FIG. 10 is an explanatory diagram illustrating a distribution arrangement unit according to the second embodiment. [Figure 9] FIG. 10 is an explanatory diagram illustrating a distribution arrangement unit according to the second embodiment. [Figure 10] FIG. 11 is a diagram showing an example of arrangement by a distribution arrangement unit according to the second embodiment. [Figure 11] FIG. 11 is a diagram showing an example of arrangement by a distribution arrangement unit according to the third embodiment. [Figure 12] FIG. 13 is a diagram showing an example of arrangement by a distribution arrangement unit according to the fourth embodiment. [Figure 13] 10A and 10B are diagrams illustrating an example of arrangement by a distribution arrangement unit according to another embodiment. [Figure 14] 10A and 10B are diagrams illustrating an example of arrangement by a distribution arrangement unit according to another embodiment. [Figure 15] 10A and 10B are diagrams illustrating an example of arrangement by a distribution arrangement unit according to another embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0033] [First embodiment] A first embodiment of the present invention will be described below with reference to the drawings. In the following description, elements having substantially the same functions or configurations will be given the same reference numerals, and redundant description may be omitted.

[0034] [Hardware configuration of information processing device 10] As shown in Fig. 1, the information processing device 10 according to the first embodiment is an information processing device 10 that processes information using intellectual property data 5 that has acquired predetermined acquired information 220 from the intellectual property data 5. Applicants are assumed to be companies, universities, research institutes, etc. Technology classifications are assumed to be IPCs that have already been classified and are available, or classifications that have been classified after the publication of an application by text mining or the like.

[0035] The information processing device 10 acquires predetermined acquired information 220 from the intellectual property data 5 via the network N, the acquired acquired information 220 is input to the information processing device 10, and the processed information processed in the information processing device 10 is output to the output device 60.

[0036] Intellectual property data 5 is a database that accumulates information on multiple publicly disclosed intellectual property. Information on intellectual property may include patent information, utility model information, design information, and trademark information. Furthermore, information on intellectual property is not limited to registered intellectual property, but may also include pending applications. Information on intellectual property may include at least one of information on publications issued by public organizations such as patent offices of each country and region (including international organizations; the same applies below), information on application progress, information on appeals, and information on litigation. Information on intellectual property may also include, for example, information that has been compiled, analyzed, etc. based on information on intellectual property issued by public organizations of each country and region.

[0037] The information processing device 10 is configured as an ECU (Electronic Control Unit) that performs various controls. The information processing device 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a storage 14, and an input / output interface (input / output I / F) 15. Each component is connected to each other via a bus 16 so as to be able to communicate with each other.

[0038] In the information processing device 10, the CPU 11 reads out a program stored in the ROM 12 and the storage 14, and executes the program while expanding it in the RAM 13, thereby realizing functions according to the program.

[0039] The input / output interface 15 is connected to an output device 60, and information processed in the information processing device 10 is output to the output device 60. The output device 60 can be, for example, an image display device, a printer, or the like.

[0040] [Functional configuration of information processing device 10] As shown in FIG. 2, the information processing device 10 functionally includes an acquisition unit 20, a calculation unit 30, a distribution generation unit 40, and a distribution arrangement unit 50.

[0041] (Acquisition part 20) As shown in FIG. 3 , the acquisition unit 20 acquires, as acquired information 220, evaluation values ​​210 for each technology category for a predetermined period for each applicant. The acquisition unit 20 acquires the acquired information 220. The acquisition unit 20 acquires, as acquired information 220, evaluation values ​​210 for a predetermined period for each technology category for a specific applicant. The evaluation values ​​210 are values ​​calculated from the number of applications, the number of published applications, the number of patents, the number of citations, the number of cited applications, and the number of application regions for each technology category, and may include at least one of the aggregate values ​​of weighted values ​​thereof. The predetermined period is, for example, from July 1, 2016 to June 30, 2018.

[0042] (Calculation unit 30) 4, the calculation unit 30 calculates an intellectual property evaluation value 310 (described later) for each technology category for a predetermined period for each applicant based on the acquired information 220. The calculation unit 30 calculates the intellectual property evaluation value 310 for each technology category based on the acquired information 220, which is composed of evaluation values ​​210 for each technology category for each applicant for a predetermined period acquired by the acquisition unit 20, and sets the calculated intellectual property evaluation value 310 as difference information 320 (described later). The calculation unit 30 uses first acquired information 220A for a predetermined period and second acquired information 220B for a period different from the first acquired information 220A to calculate, based on the acquired information 220, the difference between the evaluation value for each technology category of the second acquired information 220B based on the first acquired information 220A, and calculates a set of the intellectual property evaluation values ​​310 as difference information 320.

[0043] The calculation unit 30 uses the acquired information 220 output from the acquisition unit 20 to calculate the intellectual property evaluation value 310. The calculation unit 30 calculates the intellectual property evaluation value 310 based on the acquired information 220 relating to two different periods by the same applicant. The acquired information 220 may be composed of first acquired information 220A and second acquired information 220B relating to a period newer than the first acquired information 220A. The calculation unit 30 may create the difference between the evaluation values ​​210 for each of the same technology classifications and use this as the intellectual property evaluation value 310.

[0044] For example, in Figure 4, when the technology classification A of the second acquired information 220B has an evaluation value 210 of A2 and the technology classification A of the first acquired information 220A has an evaluation value 210 of A1, the intellectual property evaluation value 310 of the technology classification A as the difference information 320 is calculated as A2-A1.

[0045] Virtual information may be used for one of the first acquired information 220A and the second acquired information 220B. In actual calculation, there may be cases where a technology classification is not counted for one of the periods of the second acquired information 220B and the first acquired information 220A. In this case, the intellectual property evaluation value 310 may be calculated by substituting 0 as the evaluation value 210 for the period that was not counted.

[0046] In the actual calculation, technology classifications that are not counted as technology classifications in either the period of the second acquired information 220B or the period of the first acquired information 220A may be treated as if they do not exist from the beginning. In this process, by limiting the technology classifications to those that the applicant actually handled, it is possible to eliminate the impact on the distribution of technology classifications that the applicant did not handle.

[0047] (Distribution generator 40) 5, the distribution generation unit 40 generates a distribution based on the intellectual property evaluation value 310 calculated by the calculation unit 30. The distribution generation unit 40 calculates expected values ​​that characterize each distribution for a normal distribution (an example of a distribution) and values ​​related to normalized variance, generates a distribution, obtains the expected values ​​and standard deviations, and stores the normal distribution, the expected values, and the standard deviations. Note that the distribution is not limited to a normal distribution, and may be a normal skew distribution (an example of a distribution), a Poisson distribution (an example of a distribution), or the like.

[0048] The distribution generation unit 40 first calculates an expected value. Specifically, the distribution generation unit 40 calculates the expected value using the intellectual property evaluation values ​​310 of the technology classifications A, B, C, ... described in the difference information 320 calculated by the calculation unit 30, according to the following formula (1). For example, in FIG. 4, the intellectual property evaluation values ​​310 are A2-A1, B2-B1, and C2-C1. Note that there may be N technology classifications.

[0049]

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[0053] In Figure 5, a normal distribution is used, but other distributions such as T distribution, F distribution, chi-square distribution, Poisson distribution, etc. are also acceptable. By using values ​​obtained by integrating and normalizing the probability density as indicators for the rate of change in "concentration and selection" for these distributions, it is assumed that the indicators can be used to compare multiple applicants, eliminating the difference in the size of each applicant's actual portfolio, etc.

[0054] (Distribution arrangement section 50) As shown in Figure 6, the distribution placement unit 50 places the normal distribution on a three-dimensional coordinate axis, with the random variable of the normal distribution as the random variable axis A1, at least one of the expected value, standard deviation, and a weighted aggregate value of the normal distribution as the base axis A2, and the probability density of the normal distribution as the probability density axis A3. Note that in Figure 6, as an example, normal distributions for eight companies, A, B, C, D, E, F, G, and H, are placed on the three-dimensional coordinate axis consisting of the random variable axis A1, the base axis A2, and the probability density axis A3. The distribution placement unit 50 places the normal distributions of the eight competitors, represented by the probability density and random variables, with the standard deviation value as the rate of change of "concentration and selection."

[0055] Specifically, as shown in Fig. 6, the distribution allocation unit 50 executes the acquisition unit 20, calculation unit 30, and distribution generation unit 40 once or multiple times, and allocates the distribution using the rate of change of "concentration and selection" as an index. "Concentration" is determined, for example, based on the applicant's technology classification of expansion trends, and "selection" is determined, for example, based on the applicant's technology classification of contraction trends.

[0056] That is, the distribution placement unit 50 places the normal distribution on three-dimensional coordinate axes, including a random variable axis A1 that uses the normal distribution obtained by the distribution generation unit 40 as an index, a base axis A2 that is an index of the rate of change of "concentration and selection," and a probability density axis A3 that represents the probability density of the normal distribution.

[0057] By introducing an indicator of the rate of change in "concentration and selection" into axis A2 and plotting it on a single graph, it becomes possible to compare the application trends of each company under consideration.

[0058] [Relationship between standard deviation and diffusion coefficient] The validity of using standard deviation for the rate of change of the applicant's own "concentration and selection" will be explained based on the relationship between standard deviation and diffusion coefficient. The diffusion equation is expressed by equation (5).

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[0065] Equation (10) shows the relationship between standard deviation and the one-dimensional diffusion coefficient D. Equation (8) shows that the two steps of the random walk distance are divided by the time step, so the standard deviation σ (Equation (10)) has the same dimension as distance (length). Therefore, a larger standard deviation σ means a larger diffusion coefficient D, assuming the time term is constant. On the other hand, the larger the diffusion coefficient, the faster the rate of diffusion, meaning that it diffuses over a longer distance, resulting in faster progress in technology classification to the outer edge of the distribution. Therefore, a larger diffusion coefficient is considered to indicate a greater rate of change in the "concentration and selection" of applicants themselves, leading to the aforementioned statement that "the larger the standard deviation, the greater the rate of change in "concentration and selection," i.e., the more advanced the diffusion." This is the background behind using standard deviation as a single element to represent the rate of change in the "concentration and selection" of applicants themselves.

[0066] In this disclosure, we analyze applicants' application trends using a normal distribution, which is easy to calculate. However, there are limitations to fitting a situation where some force is applied, such as a company that willfully advances the development of a certain technology category (in the positive direction of the random variable) or a company that is forced to reduce the development of a certain technology category for some reason (in the negative direction of the random variable), to the simple diffusion equation (normal distribution) mentioned above. In fact, there are analysis results for applicants whose normalized distribution does not show a significant negative or positive bias, and the deviation of the actual curve from the normal distribution becomes an issue. We believe that approximating factors such as willfulness using the evolution equation of the diffusion equation will be a future challenge (see "Applied Mathematics Workbook: Numerical Analysis of Evolution Equations," by Nobuo Yajima and Tatsuo Nomoto, Iwanami Publishing).

[0067] [Processing flow by information processing device 10] 7, when the process starts, the acquisition unit 20 acquires, for each applicant, an evaluation value 210 for each technology classification for a predetermined period as acquired information 220 (step S101). Specifically, for example, for each of the eight companies, the acquisition unit 20 sets the period of first acquired information 220A as July 1, 2016 to June 30, 2018 and the period of second acquired information 220B as July 1, 2021 to June 30, 2023, and acquires the number of publications for each IPC main group as the technology classification as the evaluation value 210.

[0068] Next, the calculation unit 30 calculates an intellectual property evaluation value 310 (described later) for each applicant for each technology classification for a predetermined period based on the acquired information 220 (step S102). Specifically, for example, the calculation unit 30 calculates difference information 320 for the first acquired information 220A and the second acquired information 220B.

[0069] Next, the distribution generation unit 40 generates a distribution based on the intellectual property evaluation value 310 calculated by the calculation unit 30 (step S103). Specifically, for example, the distribution generation unit 40 performs the calculations of formulas (1) to (4) to generate a normal distribution, an expected value, and a standard deviation.

[0070] Next, the distribution arrangement unit 50 arranges the distribution (step S104) and ends the process. Specifically, for example, the distribution arrangement unit 50 arranges the normal distribution on three-dimensional coordinate axes, which are a probability variable axis A1, a base axis A2, and a probability density axis A3.

[0071] [Effect] The information processing device 10 according to the first embodiment includes an acquisition unit 20 that acquires predetermined acquired information 220 from intellectual property data 5, a calculation unit 30 that calculates an intellectual property evaluation value 310 for a predetermined period for each applicant for each technology classification based on the acquired information 220, a distribution generation unit 40 that generates a distribution based on the intellectual property evaluation value 310 calculated by the calculation unit 30, and a distribution arrangement unit 50 that arranges the distribution (see FIG. 2).

[0072] A distribution is generated for each applicant for each technology classification based on the intellectual property evaluation value 310 calculated for a predetermined period based on the acquired information 220 obtained from the intellectual property data 5, and the distribution displays the trends of technology classification for each applicant for a predetermined period. As a result, it is possible to grasp technology classifications characterized by concentration and selection for each applicant.

[0073] In the information processing device 10 according to the first embodiment, the acquisition unit 20 acquires, as the acquired information 220, an evaluation value for each applicant for each technology category over a predetermined period.

[0074] The intellectual property evaluation value 310 can be easily calculated by acquiring the evaluation value for each applicant for each technology classification for a predetermined period as acquired information 220. Therefore, it is easy to understand the technology classification characterized by the concentration and selection for each applicant.

[0075] In the information processing device 10 according to the first embodiment, the evaluation value includes at least one of the number of applications, the number of published applications, the number of patents, the number of citations, the number of times cited, and a total value of weighted values ​​thereof.

[0076] A distribution can be generated based on at least one of the number of applications, number of published applications, number of patents, number of citations, number of citations, and a weighted aggregate of these values, thereby enabling accurate understanding of technology classification characterized by concentration and selection by applicant.

[0077] In the information processing device 10 according to the first embodiment, the calculation unit 30 uses first acquired information 220A from a predetermined period and second acquired information 220B from a period different from the first acquired information 220A to calculate the difference between the evaluation value for each technology classification of the second acquired information 220B based on the first acquired information 220A as an intellectual property evaluation value 310, and calculates the set of intellectual property evaluation values ​​310 as difference information 320.

[0078] The set of intellectual property evaluation values ​​310 calculated based on the difference between the evaluation value for each technology classification of the second acquired information 220B and the first acquired information 220A is calculated as differential information 320, and the differential information 320 is reflected in the distribution. This makes it possible to grasp with even greater precision the technology classification characterized by the concentration and selection of each applicant.

[0079] In the information processing device 10 according to the first embodiment, the distribution generating section 40 generates a normal distribution as the distribution.

[0080] By generating a normal distribution as the distribution, the random variables for each technology classification are displayed in the normal distribution, which allows for a more accurate understanding of technology classifications characterized by concentration and selection for each applicant.

[0081] In the information processing device 10 according to the first embodiment, the distribution generation unit 40 generates a normal distribution based on the difference information 320, obtains the expected value and the standard deviation, and holds the normal distribution, the expected value, and the standard deviation.

[0082] The normal distribution is stored by holding the normal distribution generated based on the expected value, standard deviation, and difference information 320. Therefore, the stored normal distribution can be used to visualize the state of technology classification for each applicant. As a result, it is possible to grasp with more precision the technology classification characterized by concentration and selection for each applicant.

[0083] Incidentally, the larger the standard deviation, the smaller the intercept of the probability density axis A3 of the normal distribution curve. Standard deviation is one element that represents the degree of change in the applicant's "concentration and selection," and it is considered that the larger the standard deviation, the greater the degree of concentration. Therefore, if the normal distribution curve is displayed as is, a lower intercept of the probability density axis A3 means a higher speed, which makes it difficult to understand the degree of change in "concentration and selection."

[0084] In the information processing device 10 according to the first embodiment, the distribution placement unit 50 places the normal distribution on a three-dimensional coordinate axis, with the random variable of the normal distribution as the random variable axis A1, the expected value, standard deviation, and at least one of the aggregated values ​​of their weighted values ​​as the base axis A2, and the probability density of the normal distribution as the random density axis A3.

[0085] By plotting the normal distribution on a three-dimensional coordinate axis, with the probability variable of the normal distribution as the probability variable axis A1, the expected value, standard deviation, or at least one of the aggregated values ​​of these weighted values ​​of the normal distribution as the base axis A2, and the probability density of the normal distribution as the probability density axis A3, the normal distribution of multiple applicants is plotted along the base axis A2. This makes it possible to grasp the concentration and speed of change in selection of multiple applicants.

[0086] The information processing method according to the first embodiment acquires predetermined acquired information 220 from intellectual property data 5, calculates an intellectual property evaluation value 310 for a predetermined period for each applicant for each technology classification based on the acquired information 220, and generates a distribution based on the intellectual property evaluation value 310.

[0087] A distribution is generated for each applicant for each technology classification based on the intellectual property evaluation value 310 calculated for a predetermined period based on the acquired information 220 obtained from the intellectual property data 5. This displays the trends of technology classification for each applicant for a predetermined period. As a result, it is possible to grasp the concentration of each applicant and the selected technology classification.

[0088] The program according to the first embodiment acquires predetermined acquired information 220 from intellectual property data 5, calculates an intellectual property evaluation value 310 for a predetermined period for each applicant for each technology classification based on the acquired information 220, and causes a computer to execute a process of generating a distribution based on the intellectual property evaluation value 310.

[0089] A distribution is generated for each applicant for each technology classification based on the intellectual property evaluation value 310 calculated for a predetermined period based on the acquired information 220 obtained from the intellectual property data 5. This displays the trends of technology classification for each applicant for a predetermined period. As a result, it is possible to grasp the concentration of each applicant and the selected technology classification.

[0090] Second Embodiment The information processing device 10 according to the second embodiment differs from the first embodiment in that the configuration of the distribution unit 50 is different. Note that the same terms or the same reference numerals will be used to describe parts that are the same as or equivalent to those described in the above embodiment.

[0091] As shown in FIG. 10, the distribution arrangement unit 50 arranges the normal distribution on a two-dimensional coordinate axis, with the random variable of the normal distribution as the random variable axis A1 and at least one of the expected value, standard deviation, and the aggregated value of their weighted values ​​as the base axis A2.

[0092] In addition, the distribution placement unit 50 may place the normal distribution on a three-dimensional coordinate axis formed by the probability variable axis A1, the base axis A2, and the probability density axis A3, and then place the normal distribution on a two-dimensional coordinate axis formed by the probability variable axis A1 and the base axis A2.

[0093] Specifically, as shown in Fig. 8, the distribution allocation unit 50 can set thresholds Y1 and Y2 on the random variable axis in advance for the normal distribution. Technology classifications above the threshold Y1 are considered to be areas where applicants are "concentrating" on applications and publications, etc. Technology classifications below the threshold Y2 can be considered to be areas where applicants are "selecting" to reduce applications and publications, etc.

[0094] In Figure 8, applicant B's technology categories A and B are located above the threshold Y1, indicating that they are "concentrated." On the other hand, applicant B's technology category C is located below the threshold Y1, indicating that the applicant is reducing the number of applications and publications, etc., through "selection." Furthermore, applicant A's technology category D is located below the threshold Y1, indicating that the applicant is reducing the number of applications and publications, etc., through "selection." The expected value and standard deviation values ​​for applicant A are μA and XA, and the expected value and standard deviation values ​​for applicant B are μB and XB.

[0095] In FIG. 9, the vertical axis is a random variable axis A1, and specific thresholds Y1 and Y2 are shown. The horizontal axis represents a base axis A2 that introduces an index called the rate of change of "concentration and selection." As described in the first embodiment, the index of base axis A2 indicates a higher degree of rate of change of concentration and selection as the value increases. Base axis A2 is represented by a function F(). The function F() is defined by an expected value and a standard deviation value X, and may be expressed as the value of X itself, that is, F(μ,X)=X, for example. Furthermore, when the value of μ is positive, the function F() may be expressed as F(μ,X)=X. Furthermore, when the value of μ is negative, the function F() may be expressed as F(μ,X)=-X, for example. Note that other definitions of the function F() are also possible.

[0096] The indicator of the rate of change in "concentration and selection" can be said to express the rate of change in "concentration and selection" of the applicant itself, since it is considered that the larger the standard deviation is, the more advanced the rate of change in "concentration and selection" (i.e., the more diffused) is, based on the relationship between standard deviation and diffusion coefficient.

[0097] In Figure 9, for applicant B, technology categories A and B are located on the positive part of the random variable axis A1, and therefore can be said to be "concentrated." On the other hand, applicant B's technology category C is located on the negative part of the random variable axis A1, and therefore can be said to be reducing the number of applications and publications, etc., through "selection." Furthermore, for applicant A, technology category D is located on the negative part of the random variable axis A1, and therefore can be said to be reducing the number of applications and publications, etc., through "selection."

[0098] That is, FIG. 9 shows a comparison of the degree of change in the speed of "concentration and selection" for multiple applicants, and the technology classifications for concentration and selection for each of the multiple applicants.

[0099] As shown in Fig. 10, the distribution allocation unit 50 arranges the normal distribution on a two-dimensional coordinate axis, with the random variable of the normal distribution as the random variable axis A1 and at least one of the expected value, standard deviation, and aggregating value of their weighted values ​​as the base axis A2. Note that in Fig. 10, as an example, normal distributions for eight companies, A, B, C, D, E, F, G, and H, are arranged on the two-dimensional coordinate axis composed of the random variable axis A1 and the base axis A2. The distribution allocation unit 50 arranges the normal distributions of the eight competitors, represented by probability densities and random variables, with the standard deviation value as the rate of change of "concentration and selection."

[0100] In Figure 10, the vertical axis is the random variable axis A1, and the horizontal axis is the base axis A2, which is the standard deviation of the rate of change in "concentration and selection," and technology classifications of 3σ or more and -3σ or less are plotted. In reality, technology classifications can be clearly indicated for each plot, but this disclosure does not do so. This display makes it clear which technology classifications are concentrated for each company and which technology classifications are shrinking due to selection, making the degree of change in the rate of "concentration and selection" for each company easier to understand compared to a three-dimensional display.

[0101] In this example, Company H exhibited an extremely high rate of change in "concentration and selection." Another investigation revealed that Company H had made R&D investments during the same period and strengthened three technology categories. Furthermore, Companies B and C had negative expected values, with many technology categories below -3σ. Both companies had downsized the technology categories in which they initially excelled, and appeared to be seeking to switch to new technology categories.

[0102] Table 1 shows the results of counting the number of technology classifications that appear at 3σ or above and -3σ or below, based on the graph in Figure 10, by setting the expected value, standard deviation, and thresholds for each company as 3σ and -3σ. [Table 1]

[0103] [Effect] In the information processing device 10 according to the second embodiment, the distribution arrangement unit 50 arranges the normal distribution on a two-dimensional coordinate axis, with the random variable of the normal distribution as the random variable axis A1 and at least one of the expected value, standard deviation, and the aggregated value of their weighted values ​​as the base axis A2 (see FIG. 10).

[0104] By plotting the normal distribution on a two-dimensional coordinate axis, with the random variable of the normal distribution as the random variable axis A1 and at least one of the expected value, standard deviation, and the aggregated value of their weighted values ​​as the base axis A2, the normal distribution can be visualized in two dimensions. This allows for a better understanding of the rate of change in the concentration and selection of multiple applicants, as well as an accurate understanding of the concentration and selected technology classification for each applicant.

[0105] In other words, if a small company increases the number of applications and promotes development despite having a small portfolio to begin with, the numerical size of its portfolio will be small compared to a company that can make larger investments. However, by using a normalized value that does not represent a large change in the portfolio of a small company, it is possible to capture the degree of change in the "concentration and selection" of the applicants themselves.

[0106] Furthermore, by indicating technology categories above and below a specific threshold on the random variable axis, it is possible to clearly indicate the applicant's "concentrated" technology categories and the technology categories narrowed due to "selection," regardless of the applicant's size. In other words, if a small company, even with a small portfolio, increases the number of applications in a specific technology category and promotes development, the size of the portfolio in that specific technology category will still be small compared to a large company. However, even this modest change for a small company can be captured by clearly indicating technology categories above and below a specific threshold, allowing us to capture the "concentration and selection" of the applicant's actual concentrated technology categories. This clarifies the investment direction of each company and facilitates comparisons between companies regarding the impact of investment.

[0107] The other configurations and effects are substantially the same as those of the above embodiment, and therefore will not be described further.

[0108] Third Embodiment The information processing device according to the third embodiment differs from the above-described embodiments in that the configuration of the distribution unit is different. Note that the same or equivalent parts as those described in the above-described embodiments will be described using the same terms or the same reference numerals.

[0109] As shown in FIG. 11, the distribution arrangement unit 50 arranges the normal distribution on three-dimensional coordinate axes, with the random variable of the normal distribution as the random variable axis A1, the probability density of the normal distribution as the random density axis A3, and the time axis A4.

[0110] FIG. 11 shows the results of an analysis of changes over time for Company I. First, the acquisition unit 20 acquires the number of published items as the evaluation value 210 for each IPC main group as a technology classification for Company I. In this case, the period is set as July 1, 2011 to June 30, 2013 for the first acquired information 220A, and as July 1, 2016 to June 30, 2018 for the second acquired information 220B, and this data is used as the 2017 data.

[0111] Similarly, the period of the first acquired information 220A was set to July 1, 2011+N to June 30, 2013+N, and the period of the second acquired information 220B was set to July 1, 2016+N to June 30, 2018+N, and this data was used as the data for 2017+N. In the third embodiment, N is 1, 2, 3, 4, or 5.

[0112] Next, the calculation unit 30 calculates difference information 320 between the first acquired information 220A and the second acquired information 220B. Next, the distribution generation unit 40 performs the calculations of equations (1) to (4) to generate a normal distribution, obtain an expected value and a standard deviation, and store the normal distribution, the expected value, and the standard deviation. Next, the distribution arrangement unit 50 arranges the normal distribution of Company I, represented by the probability density and the random variable, in time series along the time axis A4.

[0113] [Effect] In the information processing device 10 according to the third embodiment, the distribution arrangement unit 50 arranges the normal distribution on three-dimensional coordinate axes, with the random variable of the normal distribution as the random variable axis A1, the probability density of the normal distribution as the random density axis A3, and the time axis A4 (see FIG. 11).

[0114] By plotting the normal distribution on a three-dimensional coordinate system with the random variable axis A1 representing the normal distribution's random variable, the random density axis A3 representing the normal distribution's random density, and the time axis A4 representing the normal distribution, the normal distribution for a given period of time for the applicant is plotted along the time axis A4, thereby making it possible to grasp the tendency of the applicant's technology classification.

[0115] The other configurations and effects are substantially the same as those of the above embodiment, and therefore will not be described further.

[0116] [Fourth embodiment] The information processing device according to the fourth embodiment differs from the above-described embodiments in that the configuration of the distribution unit is different. Note that the same or equivalent parts as those described in the above-described embodiments will be described using the same terms or the same reference numerals.

[0117] As shown in FIG. 12, the distribution arrangement unit 50 arranges the normal distribution on two-dimensional coordinate axes, with the random variable of the normal distribution being the random variable axis A1 and the time axis A4.

[0118] In Figure 12, the vertical axis represents the random variable axis A1, the horizontal axis represents the time axis A4, and technology classifications of 3σ or more and -3σ or less are plotted. In reality, technology classifications can be clearly indicated for each plot, but this disclosure does not do so. It was found that Company I has maintained the number of published applications in technology area K, but the number of published applications in technology area R, technology category B, technology category G, and technology category C, which were previously its specialties, has decreased. This shows that Company I is searching for the next technology area to focus on. This display makes it possible to understand which technology classifications have undergone concentration and selection processes.

[0119] Table 2 shows the expected value and standard deviation over time for Company I, and the results of counting the number of technology classifications that appear at 3σ or above and -3σ or below, with 3σ and -3σ set as thresholds.Table 2 shows the expected value and standard deviation for each year for Company I, and the results of counting the number of technology classifications that appear at 3σ or above and -3σ or below, with 3σ and -3σ set as thresholds, based on the graph in Figure 12.

[0120] [Table 2]

[0121] [Effect] In the information processing device 10 according to the fourth embodiment, the distribution arrangement unit 50 arranges the normal distribution on two-dimensional coordinate axes, with the random variable axis A1 representing the random variable of the normal distribution and the time axis A4 (see FIG. 12).

[0122] By plotting the normal distribution on a two-dimensional coordinate axis with the random variable of the normal distribution as the random variable axis A1 and the time axis A4, the normal distribution of the applicant over a specified period can be visualized in two dimensions. This makes it possible to grasp the transition of the applicant by technology classification.

[0123] The other configurations and effects are substantially the same as those of the above embodiment, and therefore will not be described further.

[0124] The information processing device, information processing method, and program of the present invention have been described above based on the first to fourth embodiments. However, the specific configurations are not limited to these embodiments, and design changes and the like are permitted as long as they do not deviate from the gist of the invention according to each claim in the scope of the claims.

[0125] As shown in FIG. 13, the acquisition unit may set the period for the first acquired information for Company J from July 1, 2016 to June 30, 2018, and the period for the second acquired information from July 1, 2021 to June 30, 2023. The acquisition unit may acquire the number of published items as an evaluation value for each IPC main group as a technology classification. In this case, the calculation unit may calculate differential information between the first acquired information and the second acquired information. The distribution generation unit then performs calculations according to equations (1) to (4) to generate a normal distribution, obtain the expected value and standard deviation, and store the normal distribution, expected value, and standard deviation. The distribution placement unit also places the normal distribution on a two-dimensional coordinate system consisting of a probability density axis and a probability variable axis. This display allows the technology areas in which Company J's number of published items increased by 3σ or more during this period, and the technology areas in which it decreased by -3σ or less.

[0126] Furthermore, as shown in Figure 14, the distribution allocation unit may plot technology classifications of random variables 3σ or more and -3σ or less, with the vertical axis being the random variable axis and the horizontal axis being the axis for each company. In reality, it is possible to clearly indicate the technology classification for each plot, but this is not shown in Figure 14. This display makes it clear which technology classifications are concentrated for each company and which technology classifications have been reduced by selection.

[0127] 15, the distribution unit may display the number of published items over 3σ, the number of published items between 3σ and -3σ, and the number of published items under -3σ in a bar graph on a two-dimensional coordinate system with the vertical axis representing the number of published items and the horizontal axis representing each company. This allows users to understand the actual volume of published items. [Explanation of symbols]

[0128] 5 Intellectual Property Data 10. Information processing equipment 20 Acquisition Department 30 Calculation Unit 40 Distribution generator 50 Distribution section 220 Acquisition information 220A First Acquired Information (Example of Acquired Information) 220B Second Acquired Information (Examples of Acquired Information) 310 Intellectual Property Evaluation Value 320 Difference Information A1 Stochastic variable axis A2 Core A3 Probability density axis A4 Timeline

Claims

1. an acquisition unit that acquires predetermined acquisition information from intellectual property data; a calculation unit that calculates an intellectual property evaluation value for each applicant for each technology classification for a predetermined period based on the acquired information; a distribution generation unit that generates a distribution based on the intellectual property evaluation value calculated by the calculation unit; a distribution arrangement unit that arranges the distribution; An information processing device comprising:

2. The acquisition unit acquires, for each applicant, an evaluation value for a predetermined period for each technology category as the acquired information. The information processing device according to claim 1 .

3. The evaluation value includes at least one of the number of applications, the number of published applications, the number of patents, the number of citations, the number of times cited, and a weighted aggregate value of these values. The information processing device according to claim 2 .

4. The calculation unit Based on the acquired information, using first acquired information for a predetermined period and second acquired information for a period different from the first acquired information, calculating a difference between the evaluation value of the second acquired information based on the first acquired information and the evaluation value of each technology classification as an intellectual property evaluation value; The set of intellectual property evaluation values ​​is calculated as differential information. The information processing device according to claim 2 .

5. The distribution generation unit generates a normal distribution as the distribution. The information processing device according to claim 1 .

6. The distribution generation unit generating a normal distribution based on the difference information; Obtain the expected value and standard deviation and retain the normal distribution, the expected value, and the standard deviation The information processing device according to claim 4 .

7. The distribution arrangement unit The random variable of the normal distribution is set as a random variable axis, using at least one of the expected value, standard deviation, and a weighted aggregate value of the normal distribution as a base; The normal distribution is arranged on a three-dimensional coordinate axis with the probability density of the normal distribution as the probability density axis. The information processing device according to claim 5 .

8. The distribution arrangement unit The random variable of the normal distribution is set as a random variable axis, The normal distribution is arranged on a two-dimensional coordinate axis having at least one of the expected value, the standard deviation, and the aggregate value of the weighted values ​​of the normal distribution as a base axis. The information processing device according to claim 5 .

9. The distribution arrangement unit The random variable of the normal distribution is set as a random variable axis, The probability density of the normal distribution is set as the probability density axis, The normal distribution is arranged on a three-dimensional coordinate axis with the time axis as the axis. The information processing device according to claim 5 .

10. The distribution arrangement unit The random variable of the normal distribution is set as a random variable axis, The normal distribution is arranged on a two-dimensional coordinate axis with the time axis as the axis. The information processing device according to claim 5 .

11. Obtaining the required acquisition information from intellectual property data, Based on the acquired information, an intellectual property evaluation value for each applicant for each technology classification is calculated for a predetermined period; Generate a distribution based on the intellectual property evaluation value Information processing methods.

12. Obtaining the required acquisition information from intellectual property data, Based on the acquired information, an intellectual property evaluation value for each applicant for each technology classification is calculated for a predetermined period; causing a computer to execute a process of generating a distribution based on the intellectual property evaluation value; program.

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