Technical data and patent data processing method and system

Abstract

The invention provides a technical data and patent data processing method and system. The data processing method comprises the following steps: acquiring project index data, technical index data, talent index data and resource index data of multiple technologies, and respectively acquiring associated index data and legal index data of at least one patent corresponding to the technologies; according to the project index data, the technical index data, the talent index data and the resource index data of each technology at the plurality of moments, respectively constructing a corresponding time sequence global stereo data matrix K to determine a plurality of first index values of each technology; according to the association index data and the legal index data of each patent, determining a plurality of second index values influencing the patent value; and according to each first index value of one technology and each second index value of the patent corresponding to the technology, determining the coupling degree of the technology and the patent corresponding to the technology, and determining a technology optimization scheme for improving the patent value corresponding to the technology according to the coupling degree.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular, to a method for processing technical data and patent data, a system for processing technical data and patent data, a computer program product, and a computer-readable storage medium. Background Art

[0002] With the development of technology, R & D activities have become an important driving force for social progress. The success of R & D activities depends not only on the novelty of technology, but also on other factors such as technological height, project abundance, expert density, resource intensity, patent abundance, etc. Therefore, a comprehensive evaluation and analysis of these factors is crucial for improving the efficiency and quality of R & D activities. Existing technologies mainly evaluate and analyze each element of R & D activities separately, and make corresponding optimizations and improvements according to the analysis results. For example, by analyzing the expert density, the problem of talent shortage can be found, and measures can be taken to attract and retain more outstanding talents. By analyzing the resource intensity, the problem of unreasonable resource allocation can be found, and the resource allocation can be optimized to further improve the resource utilization efficiency. However, existing technologies often ignore the mutual influence and coupling relationship among the elements when evaluating and analyzing each element of R & D activities. This leads to the possibility that when optimizing and improving one element, it may have a negative impact on other elements, thus affecting the overall efficiency and quality of R & D activities.

[0003] In order to overcome the above-mentioned defects existing in the prior art, there is an urgent need in this field for an improved data processing method for comprehensively, systematically and accurately determining a technical optimization plan for enhancing the corresponding patent value of a technology during the engineering application and industrialization process, so as to improve the overall efficiency and quality of R & D activities. Summary of the Invention

[0004] The following presents a brief overview of one or more aspects to provide a basic understanding of these aspects. This overview is not an exhaustive survey of all contemplated aspects, and is neither intended to identify key or decisive elements of all aspects nor to attempt to define the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that follows.

[0005] In order to overcome the above-mentioned defects of the prior art, the present invention provides a data processing method, a data processing system, a computer program product and a computer-readable storage medium, which can analyze the coupling relationship between multiple objective indicator data of each technology and multiple objective indicator data of each patent, so as to comprehensively, systematically, objectively and accurately determine the technical optimization plan for improving the corresponding patent value of the technology in the process of engineering application and industrialization, so as to utilize the objective laws between various technical indicator data and various patent indicator data representing the patent value to improve the overall efficiency and quality of R&D activities.

[0006] Specifically, the data processing method provided according to the first aspect of the present invention includes the following steps: obtaining project indicator data, technical indicator data, talent indicator data and resource indicator data of multiple technologies, and respectively obtaining the associated indicator data and legal indicator data of at least one corresponding patent; constructing corresponding time-series global three-dimensional data matrices K according to the project indicator data, technical indicator data, talent indicator data and resource indicator data of each of the technologies at multiple moments to determine multiple first indicator values ​​of each of the technologies; determining multiple second indicator values ​​that affect the patent value according to the associated indicator data and legal indicator data of each of the patents; and determining the coupling degree between the technology and its corresponding patent according to each of the first indicator values ​​of a technology and each of the second indicator values ​​of its corresponding patent, and determining a technical optimization plan for improving the corresponding patent value of the technology accordingly.

[0007] Further, in some embodiments of the present invention, the project indicator data of the scientific research project includes at least one of the number of projects, internal scientific research funds, and external collaborative funds. The technical indicator data of the scientific research project includes the technical resource index and / or the achievement coefficient. The talent indicator data of the scientific research project includes the leading talent level coefficient and / or the total man-hour investment. The resource indicator data of the scientific research project includes at least one of the academic platform coefficient, the laboratory coefficient, and the industrialization coefficient. The associated indicator data of the patent includes at least one of the number of cited prior patents, the number of backward patent citations, the number of patents with at least one of the same priority, and the number of patents in the same family. The legal indicator data of the patent includes at least one of the number of document pages, the number of claims, and the number of words in the claims.

[0008] Further, in some embodiments of the present invention, the temporal global stereo data matrix k is expressed as:

[0009]

[0010] Where t=1,2,…,T represents the corresponding time. tThey are the project index variables, technical index variables, talent index variables, and resource index variables for each of the said technologies. N is the total number of the said multiple technologies. P is the total number of index variables of the project index data, technical index data, talent index data, and resource index data involved in the said multiple technologies.

[0011] Further, in some embodiments of the present invention, the step of determining multiple first index values for each of the said technologies includes: performing a principal component analysis on the time-series three-dimensional data matrix K via SPSS software to determine a normalized matrix K'. Each element x t' in the normalized matrix k' has a value between 0 and 1; according to the values of each element x t' in the normalized matrix k', multiple first index values for each of the said technologies are determined.

[0012] Further, in some embodiments of the present invention, the step of respectively determining multiple second index values that affect the patent value according to the associated index data and legal index data of each of the said patents includes: performing a deviation standardization operation on the associated index data and legal index data of each of the said patents with respect to time:

[0013]

[0014] where n is the serial number of the said technology. q is the serial number of the associated index variable and legal index variable of the said patent. x nq is the associated index variable and legal index variable of the said patent before the deviation standardization operation. x' nq is the associated index variable and legal index variable of the said patent after the deviation standardization operation; and according to the associated index data and legal index data after the deviation standardization operation, the second index values of their impacts on the patent value are respectively calculated.

[0015] Further, in some embodiments of the present invention, the step of respectively calculating the second index values of their impacts on the patent value according to the associated index data and legal index data after the deviation standardization operation includes: respectively calculating the characteristic weights of each of the said technologies for each of the second index values of the corresponding patent according to the associated index data and legal index data after the deviation standardization operation; respectively calculating the entropy values of each of the second index values according to the characteristic weights of each of the said technologies for each of the second index values of the corresponding patent to determine the corresponding difference coefficients; respectively calculating the normalized weight coefficients corresponding to each of the second index values according to the difference coefficients of each of the second index values; and respectively determining the second index values of their impacts on the patent value according to the product of each of the associated index data and each of the legal index data after the deviation standardization operation and their corresponding normalized weight coefficients.

[0016] Further, in some embodiments of the present invention, the step of determining the coupling degree between the technology and its corresponding patent according to each of the first index values of the technology and each of the second index values of its corresponding patent includes: calculating the correlation coefficient between each of the first index values of the technology and each of the second index values of its corresponding patent according to each of the first index values of the technology and each of the second index values of its corresponding patent; and calculating the coupling degree between the technology and its corresponding patent according to the correlation coefficient between each of the first index values of the technology and each of the second index values of its corresponding patent.

[0017] Further, in some embodiments of the present invention, the step of determining the technology optimization scheme includes: comparing the coupling degree between the technology and its corresponding patent with a preset threshold; in response to the coupling degree between the technology and its corresponding patent being less than the preset threshold, adjusting at least one of the project index data, technology index data, talent index data, and resource index data of the technology, and recalculating the coupling degree between it and its corresponding patent; and in response to the adjusted coupling degree of the technology being greater than or equal to the preset threshold, outputting the adjusted project index data, technology index data, talent index data, and / or resource index data as a technology optimization scheme for enhancing the value of the corresponding patent of the technology.

[0018] In addition, the above data processing system provided by the second aspect of the present invention includes a memory and a processor. A computer instruction is stored on the memory. The processor is connected to the memory and is configured to execute the computer instruction stored on the memory to implement the data processing method provided by the first aspect of the present invention.

[0019] In addition, the above computer program product provided by the third aspect of the present invention includes a computer instruction. When the computer instruction is executed by a processor, the data processing method provided by the first aspect of the present invention is implemented.

[0020] In addition, the above computer-readable storage medium provided by the fourth aspect of the present invention has a computer instruction stored thereon. When the computer instruction is executed by a processor, the data processing method provided by the first aspect of the present invention is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] After reading the detailed description of the embodiments of the present disclosure in conjunction with the following drawings, the above features and advantages of the present invention can be better understood. In the drawings, the components are not necessarily drawn to scale, and components with similar related characteristics or features may have the same or similar reference numerals.

[0022] Figure 1The flowchart shows a data processing method provided according to some embodiments of the present invention.

[0023] Figure 2 The schematic diagram shows the principle of an optimized coordination level provided according to some embodiments of the present invention. Detailed implementation manners

[0024] The following specific embodiments illustrate the implementation manners of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Although the description of the present invention will be introduced in conjunction with preferred embodiments, this does not mean that the features of this invention are limited to this implementation manner. On the contrary, the purpose of introducing the invention in conjunction with the implementation manner is to cover other alternatives or modifications that may be extended based on the claims of the present invention. To provide a deep understanding of the present invention, many specific details will be included in the following description. The present invention can also be implemented without these details. In addition, to avoid confusing or obscuring the key points of the present invention, some specific details will be omitted in the description.

[0025] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "mounted", "connected", and "coupled" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0026] In addition, the "upper", "lower", "left", "right", "top", "bottom", "horizontal", and "vertical" used in the following description should be understood as the orientations shown in this section and the related drawings. This relative term is only for convenience of description and does not represent that the device described needs to be manufactured or operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention.

[0027] It can be understood that although terms such as "first", "second", and "third" can be used herein to describe various components, regions, layers, and / or parts, these components, regions, layers, and / or parts should not be limited by these terms, and these terms are only used to distinguish different components, regions, layers, and / or parts. Therefore, the first component, region, layer, and / or part discussed below can be referred to as the second component, region, layer, and / or part without departing from some embodiments of the present invention.

[0028] As described above, the existing technologies mainly evaluate and analyze each element of R & D activities separately, and carry out corresponding optimization and improvement according to the analysis results. For example, by analyzing the expert density, the problem of talent shortage can be found, and then measures can be taken to attract and retain more outstanding talents. By analyzing the resource intensity, the problem of unreasonable resource allocation can be found, and then the resource allocation can be optimized to further improve the resource utilization efficiency. However, when evaluating and analyzing each element of R & D activities, the existing technologies often ignore the mutual influence and coupling relationship between them. This leads to the possibility that when optimizing and improving one element, it may have a negative impact on other elements, thus affecting the overall efficiency and quality of R & D activities.

[0029] In order to overcome the above-mentioned defects existing in the existing technologies, the present invention provides a data processing method, a data processing system, a computer program product and a computer-readable storage medium, which can analyze according to the coupling relationship between various objective index data of each technology and various objective index data of each patent, so as to comprehensively, systematically, objectively and accurately determine the technical optimization scheme for enhancing the corresponding patent value of the technology in the process of engineering application and industrialization, and utilize the objective law between each technical index data and each patent index data representing the patent value to improve the overall efficiency and quality of R & D activities.

[0030] In some non-limiting embodiments, the above-mentioned data processing method provided by the first aspect of the present invention can be implemented based on the above-mentioned data processing system provided by the second aspect of the present invention. The data processing system includes a memory and a processor. The memory includes, but is not limited to, the above-mentioned computer-readable storage medium provided by the fourth aspect of the present invention, on which computer instructions are stored. The processor is connected to the memory and is configured to execute the computer instructions stored on the memory to implement the data processing method provided by the first aspect of the present invention.

[0031] In addition, in some non-limiting embodiments, the above-mentioned computer program product provided by the third aspect of the present invention includes computer instructions. Here, when the computer instructions are executed by a processor, the data processing method provided by the first aspect of the present invention is implemented.

[0032] Please refer to Figure 1 and Table 1. Figure 1 FIG. shows a schematic flow chart of a data processing method provided according to some embodiments of the present invention. Table 1 shows an index table of technologies and patents provided according to some embodiments of the present invention.

[0033] Table 1 Index Table of Technologies and Patents

[0034]

[0035]

[0036] As Figure 1 shown in Table 1, the processor may first obtain the project index data, technical index data, talent index data, and resource index data of multiple technologies, and respectively obtain the associated index data and legal index data of at least one patent corresponding thereto. Herein, the multiple technologies constitute a technology set N, and the technology serial number n ∈ N.

[0037] Further, in the embodiment shown in Table 1, the project index data of the above scientific research project includes at least one of objective data such as the number of projects, internal scientific research funds, and external cooperation funds.

[0038] In addition, in the embodiment shown in Table 1, the technical index data of the above scientific research project includes a technical resource index and / or an achievement coefficient. Herein, the technical index data reflects the technical ability of the scientific research project. When the technical ability of the scientific research project is stronger, the technical resource index is higher. For example, when the technology industry chain alliance is the leading unit of the scientific research project, the technical resource index is 10. When the technology industry chain alliance is the overall technical design unit of the scientific research project, the technical resource index is 8. When the technology industry chain alliance is the participating technology R & D unit of the scientific research project, the technical resource index is 6. In other cases, the technical resource index can be set to 1-5 by analogy. In addition, when the achievement of the scientific research project is better, the achievement coefficient is higher. For example, when the achievement is national level, the achievement coefficient is 10. When the achievement is group level, the achievement coefficient is 5. When the achievement is company level, the achievement coefficient is 4.

[0039] In addition, in the embodiment shown in Table 1, the talent index data of the above scientific research project includes a leading talent level coefficient and / or the total man-hour input. Herein, the talent index data is used to indicate high-end talents with outstanding professional abilities, rich experience, and innovative spirits in a certain field. When the talent level responsible for the scientific research project is higher, the leading talent level coefficient is higher. For example, when the talent responsible for the scientific research project is a national leading talent, the leading talent level coefficient is 10. When the talent responsible for the scientific research project is a regional or group leading talent, the leading talent level coefficient is 6. When the talent responsible for the scientific research project is a company-level leading talent, the leading talent level coefficient is 5. In addition, when the total man-hour input is higher, the total man-hour input coefficient is higher. For example, when the total man-hour input is 200 days / year, the total man-hour input coefficient is 10. When the total man-hour input is 150 days / year, the total man-hour input coefficient is 8. When the total man-hour input is 100 days / year, the total man-hour input coefficient is 6.

[0040] In addition, in the embodiment shown in Table 1, the resource indicator data of the above scientific research project includes at least one of the academic platform coefficient, laboratory coefficient, and industrialization coefficient. Here, the resource indicator data of the scientific research project is a reflection of the degree of configuration of scientific research resources and infrastructure. The better the configuration, the greater the academic platform coefficient, laboratory coefficient, and industrialization coefficient. For example, when the academic platform of the scientific research project is at the national level, the academic platform coefficient and laboratory coefficient are 10. When the academic platform of the scientific research project is at the association level, the academic platform coefficient and laboratory coefficient are 7. When the academic platform of the scientific research project is at the group level, the academic platform coefficient and laboratory coefficient are 6. When the academic platform of the scientific research project is at the regional or company level, the academic platform coefficient and laboratory coefficient are 5. In addition, when industrialization develops into an independent legal person company, the industrialization coefficient is 10. When the industrialization economic volume is greater than 10 million yuan, the industrialization coefficient is 8. When the industrialization economic volume is less than 10 million yuan and greater than 6 million yuan, the industrialization coefficient is 6. When the industrialization economic volume is less than 6 million yuan and greater than 3 million yuan, the industrialization coefficient is 5.

[0041] In addition, in the embodiment shown in Table 1, the associated indicator data of the above patents include at least one of objective data such as the number of cited prior patents, the number of backward citations of patents, the number of patents with at least one same priority, and the number of patents in the same family.

[0042] In addition, in the embodiment shown in Table 1, the legal indicator data of the above patent includes at least one of the number of document pages, the number of claims, and the number of words in the claims.

[0043] Afterwards, the processor constructs the corresponding time-series global three-dimensional data matrix K according to the project indicator data, technical indicator data, talent indicator data and resource indicator data of each technology at multiple times, so as to determine multiple first indicator values ​​N of each technology. p (n) Here, the multiple moments constitute a moment set T, and the moment sequence number t∈T. Each indicator variable related to the technology constitutes a first indicator variable set P, and the first indicator variable sequence number p∈P.

[0044] Specifically, in some preferred embodiments, the present invention can divide the samples at each moment into units of day, week, month, quarter, and year according to the time period of technology research and development.

[0045] Furthermore, in some embodiments, the above-mentioned temporal global stereo data matrix K is expressed as:

[0046]

[0047] Where t=1,2,…,T represents the corresponding time. tFor the project index variables, technical index variables, talent index variables, and resource index variables of each technology, that is, the first index variables. N is the total number of multiple technologies. P is the total number of index variables of the project index data, technical index data, talent index data, and resource index data involved in multiple technologies.

[0048] Specifically, in the embodiment shown in Table 1, x t is the x in Table 1 11 ~x 19 , and P = 9.

[0049] Furthermore, in the process of determining the multiple first index values N p (n) of each technology, the processor can perform principal component analysis on the time - series three - dimensional data matrix K through the Statistical Package for the Social Sciences (SPSS) software to determine the normalized matrix K'.

[0050] Here, the value of each element x t' in the normalized matrix K' is between 0 and 1.

[0051] In this way, the present invention can perform principal component analysis on the above - mentioned time - series three - dimensional data matrix K to normalize each first index, so as to eliminate the influence of dimension differences and numerical interval differences on the computability between each first index value.

[0052] After that, the processor can determine the multiple first index values N t' of each technology according to the values of each element x p (n)=x np '. Here, n = 1, 2, …, N, p = 1, 2, …, P.

[0053] Then, the processor can respectively determine the multiple second index values K q (n) that affect the patent value according to the associated index data and legal index data of each patent. Here, the index variables related to each patent constitute the second index variable set Q, and the second index variable serial number q ∈ Q.

[0054] Further, in the process of determining the multiple second index values K q (n) of each patent, the processor can first perform deviation standardization operation on the associated index data and legal index data of each patent with respect to time:

[0055]

[0056] Among them, n is the serial number of the technology, and q is the serial number of the correlation index variable and legal index variable of the patent. x nq is the correlation index variable and legal index variable of the patent before the deviation standardization operation. x' nq is the correlation index variable and legal index variable of the patent after the deviation standardization operation.

[0057] Specifically, in the embodiment shown in Table 1, q = 1, 2, …, 6, and x nq is the x in Table 1 21 ~x 26 .

[0058] In this way, the present invention can perform deviation standardization operations on the correlation index data and legal index data of the above-mentioned patents with respect to time, determine the index weights according to the amount of information provided by each index data, and be used to reflect the utility value of the index information entropy value, avoiding human influence factors, so that the index weights are more objective.

[0059] After that, the processor can calculate the second index value of its influence on the patent value respectively according to the correlation index data and legal index data after the deviation standardization operation. Here, the correlation index data is the value of the correlation index variable after the deviation standardization operation. The legal index data is the value of the legal index variable after the deviation standardization operation.

[0060] In addition, in some preferred embodiments, the processor can first calculate the characteristic proportion P of each second index value of each technology for the corresponding patent according to the correlation index data and legal index data after the deviation standardization operation nq :

[0061]

[0062] Among them, x nq '≥0, and N is the total number of technologies in the patent set.

[0063] After that, the processor can calculate the entropy value e of each second index value respectively according to the characteristic proportion P of each second index value of each technology for the corresponding patent nq , so as to determine the corresponding difference coefficient g q : q :

[0064]

[0065] g q = 1 - e q

[0066] Among them, k = 1 / lnN.

[0067] After that, the processor can calculate the corresponding normalized weight coefficient ω for each second index value according to the difference coefficient g q : q :

[0068]

[0069] where Q is the total number of associated index variables and legal index variables involved in each patent.

[0070] After that, the processor can determine the second index value K of its impact on the patent value according to each associated index data and each legal index data after the deviation normalization operation, and the product of their corresponding normalized weight coefficients ω q : q (n):

[0071] K q (n) = x nq ’ * ω q

[0072] where n = 1, 2, …, N, q = 1, 2, …, Q.

[0073] After that, the processor can determine the coupling degree D(n) between a technology and its corresponding patent according to each first index value of the technology and each second index value of its corresponding patent.

[0074] Specifically, the processor can calculate the correlation coefficient ξ p (n) between each first index value of the technology and each second index value of its corresponding patent according to each first index value N q (n) of the technology and each second index value K pq (n) of its corresponding patent:

[0075]

[0076] where β is the discrimination coefficient, usually taking a value of 0.5.

[0077] After that, the processor can calculate the coupling degree D(n) between the technology and its corresponding patent according to the correlation coefficient ξ pq (n) between each first index value of the technology and each second index value of its corresponding patent:

[0078]

[0079] where the value of D(n) ranges from 0 to 1.

[0080] Please refer to Figure 2 and Table 2. Figure 2The schematic diagram of the principle of optimizing the coordination level provided according to some embodiments of the present invention is shown. Table 2 shows the coupling degree level table provided according to some embodiments of the present invention.

[0081] Table 2 Coupling Degree Level Table

[0082]

[0083]

[0084] After that, as Figure 2 shown in Table 2, the processor can determine the technical optimization plan for enhancing the corresponding patent value of the technology according to the coupling degree D(n) between the technology calculated above and its corresponding patent.

[0085] Specifically, the processor can compare the coupling degree between the technology and its corresponding patent with a preset threshold (for example: 0.6).

[0086] After that, in response to the coupling degree between the technology and its corresponding patent being less than the preset threshold, the processor can adjust at least one of the item index data, technical index data, talent index data, and resource index data of the technology, and recalculate the coupling degree D(n) between it and its corresponding patent.

[0087] As Figure 2 shown in Table 1, the processor can, in the normal loop process, judge the strength of multiple primary indicators between the technology and its corresponding patent according to the coordination level corresponding to the coupling degree between the technology and its corresponding patent, and correspondingly adjust multiple secondary indicators. In addition, the processor can also, in the feedback loop process, reinforce each primary indicator and re-evaluate the adjusted coordination level to adjust the coupling degree between the technology and its corresponding patent.

[0088] Alternatively, in response to the adjusted coupling degree of the technology being greater than or equal to the preset threshold, the processor can output the adjusted item index data, technical index data, talent index data, and / or resource index data as the technical optimization plan for enhancing the corresponding patent value of the technology.

[0089] In this way, the present invention can avoid the imbalance of the coordination level between the technology and its corresponding patent by cyclically adjusting at least one of the item index data, technical index data, talent index data, and resource index data of the technology, thereby improving the accuracy of the obtained technical optimization plan.

[0090] Furthermore, in some preferred embodiments, during the process of comparing the coupling degree with the preset threshold, the processor can first calculate the coupling coordination degree X of the technology at the current moment t and the previous moment t - 1 respectively according to the coupling degrees of the technology and its corresponding patent at the current moment t and the previous moment t - 1 m(t), X m (t - 1).

[0091] After that, the processor can calculate the coupling coordination degree X m (t), X m (t - 1) of multiple technologies at the current moment t and the previous moment t - 1, and calculate the σ of multiple technologies at the current moment t and the previous moment t - 1 t :

[0092]

[0093] Then, in response to the σ of multiple technologies at the current moment t t , being greater than or equal to its σ at the previous moment t - 1 t-1 , the processor can determine that the coupled coordinated development of the technology and its corresponding patent does not converge, and correct the outliers of at least one of the project index data, technical index data, talent index data, and resource index data of the technology.

[0094] Alternatively, in response to the σ of multiple technologies at the current moment t t , being greater than or equal to its σ at the previous moment t - 1 t-1 , the processor can determine that the coupled coordinated development of the technology and its corresponding patent converges, and then compare the coupling degree of the technology and its corresponding patent with a preset threshold.

[0095] In this way, the present invention can enhance the coordination of the technology optimization scheme and the interaction between elements by performing convergence analysis on the coupling degree of the technology and its corresponding patent, thereby improving the accuracy of the obtained technology optimization scheme.

[0096] In summary, the above data processing method, data processing system, computer program product, and computer-readable storage medium provided by the present invention can all comprehensively, systematically, objectively, and accurately determine the technology optimization scheme for enhancing the value of the corresponding patent of the technology by analyzing the coupling relationship between various objective index data of each technology and various objective index data of each patent, so as to utilize the objective law between each technical index data and each patent index data representing the patent value to improve the overall efficiency and quality of the R & D activity.

[0097] Although the above methods are illustrated and described as a series of actions for simplicity of explanation, it should be understood and appreciated that these methods are not limited by the order of the actions, because according to one or more embodiments, some actions may occur in a different order and / or concurrently with other actions not illustrated and described herein but understandable by those skilled in the art.

[0098] Those skilled in the art will appreciate that information, signals, and data can be represented using any of a variety of different technologies and techniques. For example, the data, instructions, commands, information, signals, bits, symbols, and chips described throughout the above description may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or optical particles, or any combination thereof.

[0099] Those skilled in the art will further appreciate that the various illustrative logical blocks, modules, circuits, and algorithmic steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability of hardware and software, the various illustrative components, blocks, modules, circuits, and steps are described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and the design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

[0100] The various illustrative logical modules and circuits described in connection with the embodiments disclosed herein can be implemented or performed with a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gates or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.

[0101] The steps of a method or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of both. The software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read from, and write to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.

[0102] In one or more exemplary embodiments, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted via a computer-readable medium as one or more instructions or code. The computer-readable medium includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. The storage media may be any available media that can be accessed by a computer. By way of example and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. As used herein, disk and disc include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk, and Blu-ray disc where disks typically reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0103] The foregoing description of the disclosure has been provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for processing technical data and patent data, characterized in that: The following steps are involved: Obtain project indicator data, technical indicator data, talent indicator data and resource indicator data of multiple technologies, and respectively obtain the associated indicator data and legal indicator data of at least one corresponding patent; According to the project indicator data, technical indicator data, talent indicator data and resource indicator data of each of the technologies at multiple times, respectively construct corresponding time series global three-dimensional data matrices K to determine multiple first indicator values ​​of each of the technologies; Determine, according to the associated indicator data and legal indicator data of each of the patents, a plurality of second indicator values ​​affecting the patent value; and According to each of the first indicator values ​​of a technology and each of the second indicator values ​​of its corresponding patent, the coupling degree between the technology and its corresponding patent is determined, and accordingly a technical optimization plan for improving the value of the corresponding patent of the technology is determined.

2. The processing method according to claim 1, characterized in that The project indicator data of the scientific research project includes at least one of the project quantity, internal scientific research funds, and external collaboration funds. The technical indicator data of the scientific research project include technical resource index and / or achievement coefficient. The talent index data of the scientific research project includes the leading talent level coefficient and / or the total man-hour input. The resource indicator data of the scientific research project includes at least one of the academic platform coefficient, laboratory coefficient and industrialization coefficient. The patent-related indicator data includes at least one of the number of cited prior patents, the number of backward patent citations, the number of patents with at least one same priority, and the number of patents in the same family. The legal indicator data of the patent includes at least one of the number of document pages, the number of claims, and the number of words in the claims.

3. The processing method according to claim 1, characterized in that: The temporal global stereo data matrix K is expressed as: Among them, t=1,2,…,T, represents the corresponding time, x t are the project indicator variables, technical indicator variables, talent indicator variables and resource indicator variables of each of the technologies, N is the total number of the multiple technologies, and P is the total number of indicator variables of the project indicator data, technical indicator data, talent indicator data and resource indicator data involved in the multiple technologies.

4. The processing method according to claim 3, characterized in that: The step of determining a plurality of first indicator values ​​for each of the technologies includes: The SPSS software is used to perform principal component analysis on the time series stereo data matrix K to determine the normalized matrix K', where: Normalize the elements x in the matrix K' t ' is between 0 and 1; and According to the elements x in the normalized matrix K' t ', determine multiple first indicator values ​​of each of the technologies.

5. The processing method according to claim 1, characterized in that: The step of determining a plurality of second indicator values ​​affecting the patent value according to the associated indicator data and legal indicator data of each of the patents comprises: The time-dependent deviation normalization operation is performed on the associated indicator data and legal indicator data of each patent: Where n is the serial number of the technology, q is the serial number of the associated indicator variable and legal indicator variable of the patent, and x nq are the associated indicator variables and legal indicator variables of the patent before the deviation standardization operation, x' nq are the associated indicator variables and legal indicator variables of the patent after the deviation standardization operation; and According to the associated index data and legal index data subjected to the deviation normalization operation, the second index values ​​of their impact on the patent value are calculated respectively.

6. The processing method according to claim 5, characterized in that: The step of respectively calculating the second indicator value of the impact on the patent value based on the associated indicator data and the legal indicator data after the deviation normalization operation comprises: Calculate the characteristic weight of each of the second indicator values ​​of each of the technologies corresponding to the patents according to the associated indicator data and the legal indicator data after the deviation normalization operation; According to the characteristic weight of each of the second index values ​​of the corresponding patents to each of the technologies, the entropy value of each of the second index values ​​is calculated to determine the corresponding difference coefficient; Calculating the corresponding normalized weight coefficients according to the difference coefficients of the second index values; and According to the products of the associated index data and the legal index data after the deviation normalization operation and their corresponding normalized weight coefficients, the second index values ​​of their impact on the patent value are determined respectively.

7. The processing method according to claim 1, characterized in that: The step of determining the coupling degree between the technology and its corresponding patent according to each of the first indicator values ​​of the technology and each of the second indicator values ​​of its corresponding patent comprises: According to each of the first index values ​​of a technology and each of the second index values ​​of its corresponding patent, calculate the correlation coefficient between each of the first index values ​​of the technology and each of the second index values ​​of its corresponding patent; and The coupling degree between the technology and its corresponding patent is calculated according to the correlation coefficient between the first indicator values ​​of the technology and the second indicator values ​​of its corresponding patent.

8. The processing method according to claim 7, characterized in that: The steps of determining the technical optimization solution include: Comparing the coupling degree between the technology and its corresponding patent with a preset threshold; In response to the coupling degree between the technology and its corresponding patent being less than the preset threshold, adjusting at least one of the project indicator data, technical indicator data, talent indicator data, and resource indicator data of the technology, and recalculating the coupling degree between the technology and its corresponding patent; and In response to the coupling degree of the technology after adjustment being greater than or equal to the preset threshold, the adjusted project indicator data, technical indicator data, talent indicator data and / or resource indicator data are output as a technical optimization solution to enhance the corresponding patent value of the technology.

9. A system for processing technical data and patent data, characterized in that: include: a memory having computer instructions stored thereon; as well as A processor is connected to the memory and is configured to execute computer instructions stored in the memory to implement the data processing method according to any one of claims 1 to 8.

10. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by a processor, the method for processing technical data and patent data according to any one of claims 1 to 8 is implemented.

11. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the computer instructions are executed by a processor, the method for processing technical data and patent data according to any one of claims 1 to 8 is implemented.

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