CN116757885B - Enterprise intellectual property dimension review system - Google Patents
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Abstract
The invention relates to an enterprise intellectual property dimension review system, belongs to the technical field of enterprise intellectual property dimension review, and solves the problems of instantaneity, objectivity, transverse comparability of review results and the like of enterprise intellectual property dimensions in the review process. The system comprises: the parameter acquisition module is used for acquiring intellectual property dimension parameters of enterprises on the intellectual property dimension data retrieval platform; the primary review module is used for obtaining primary review results of the intellectual property dimension of the enterprise based on the intellectual property dimension parameters; the distribution analysis module is used for carrying out distribution analysis on the primary review result to obtain the skewness distribution of the primary review result of the enterprise on the platform; the deviation adjusting module is used for performing deviation adjustment on the primary review result of the enterprise on the platform when the deviation distribution is non-preset distribution; the visual display module is used for visually displaying primary review results in preset distribution or review results after deviation adjustment in non-preset distribution.
Description
Technical Field
The invention relates to the technical field of enterprise intellectual property dimension review, in particular to an enterprise intellectual property dimension review system.
Background
Currently, in various application scenarios, enterprise intellectual property dimension review is required. Illustratively, during an enterprise IPO, the relevant departments will review the status of the enterprise intellectual property dimension. At present, the evaluation of the intellectual property dimension of the enterprise is mainly realized by expert scoring, and the real-time performance and objectivity are difficult to ensure.
In addition, in the process of evaluating the intellectual property dimensionality of the enterprise according to the existing mode, the evaluation standards are difficult to unify, the evaluation results are mutually independent, the evaluation results of the intellectual property dimensionality of different enterprises are large in variability, and the evaluation result data are not necessarily accurate, so that the distribution situation of the primary evaluation results of the intellectual property dimensionality of all enterprises on the platform is difficult to be well measured, and meanwhile, the transverse comparison of the intellectual property dimensionality among the enterprises is difficult to be realized.
Therefore, how to ensure the real-time performance and objectivity of the intellectual property dimension of the enterprise in the review process and the transverse comparability of the review result is a technical problem which needs to be solved at present.
Disclosure of Invention
In view of the above analysis, the embodiment of the invention aims to provide an enterprise intellectual property dimension review system, which is used for solving the problems that the real-time performance and objectivity of the enterprise intellectual property dimension in the review process, the transverse comparability of the review result and the like are difficult to ensure in the existing mode.
The invention discloses an enterprise intellectual property dimension review system, which comprises:
The parameter acquisition module is used for acquiring intellectual property dimension parameters of enterprises on the intellectual property dimension data retrieval platform by calling a database of the intellectual property dimension data retrieval platform;
The primary review module is used for obtaining a primary review result of the intellectual property dimension of the enterprise based on the acquired intellectual property dimension parameter of the enterprise;
the distribution analysis module is used for carrying out distribution analysis on the primary review result to obtain the skewness distribution of the primary review result of the enterprise on the intellectual property dimension data retrieval platform; the skewness distribution is preset distribution or non-preset distribution;
The deviation adjusting module is used for performing deviation adjustment on the primary review result of the enterprise on the intellectual property dimension data retrieval platform when the deviation distribution is non-preset distribution;
The visual display module is used for visually displaying primary review results in preset distribution or review results after deviation adjustment in non-preset distribution.
Based on the scheme, the invention also makes the following improvements:
further, in the distribution analysis module, a bias distribution S of the primary review results of the enterprise on the intellectual property dimension data retrieval platform is obtained according to the following formula:
Wherein N represents the total number of enterprises on the intellectual property dimension data retrieval platform, P n represents the primary review result of the nth enterprise on the intellectual property dimension data retrieval platform, and mu and sigma respectively represent the mean value and standard deviation of the primary review results of all enterprises on the intellectual property dimension data retrieval platform.
Further, when the value range of the skewness distribution is between [ -a, a ], the skewness distribution is a preset distribution, and a is a positive number smaller than 1;
Otherwise, the skewness distribution is a non-preset distribution.
Further, the types of the non-preset distribution include a moderate positive bias, a moderate negative bias, a high positive bias or a high negative bias distribution, and the corresponding bias adjustment is performed based on the non-preset distribution of different types.
Further, in the skewness adjustment module,
When the skewness distribution is a moderate positive skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (2):
Wherein P n' represents the evaluation result of the nth enterprise after the bias adjustment;
when the skewness distribution is a moderate negative skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (3):
wherein P MAX represents the maximum value of primary review results in all enterprises on the intellectual property dimension data retrieval platform;
when the skewness distribution is high positive skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (4):
Pn′＝k1*lnPn (4)
Wherein k 1 represents a height positive bias adjustment coefficient;
When the skewness distribution is high negative skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (5):
Pn′＝k2*ln(PMAX-Pn) (5)
Where k 2 denotes a high negative bias adjustment coefficient.
Further, the primary review module includes:
the parameter normalization unit is used for carrying out normalization processing on the intellectual property dimension parameters to obtain the intellectual property dimension normalization parameters of each enterprise;
the operation unit is used for operating the intellectual property dimension normalization parameters to obtain a first review result of the intellectual property dimension of each enterprise;
The boundary adjustment judging unit is used for respectively comparing the intellectual property dimension parameter of each enterprise with a preset boundary condition and judging whether the corresponding enterprise needs boundary adjustment or not; if the judgment result is that the corresponding enterprise does not need to carry out boundary adjustment, the first review result of the intellectual property dimension of the corresponding enterprise is directly used as the primary review result of the intellectual property dimension of the corresponding enterprise.
Further, the primary review module further comprises a boundary adjusting unit;
The boundary adjustment judging unit is further configured to generate a boundary adjustment rule of the corresponding enterprise if the judging result indicates that the corresponding enterprise needs to perform boundary adjustment;
The boundary adjusting unit is used for carrying out boundary adjustment on the first review result of the intellectual property dimension of the corresponding enterprise according to the boundary adjusting rule of the corresponding enterprise; and the result of the first review result of the intellectual property dimension of the corresponding enterprise after the boundary adjustment is used as a primary review result of the intellectual property dimension of the corresponding enterprise.
Further, the intellectual property dimension parameter comprises a plurality of first-level indexes, each first-level index is subdivided into a plurality of lower-level indexes, wherein the type of the last-level index is a proportional type or a non-proportional type, and the proportional type is a maximum proportional type or a minimum proportional type;
in the parameter normalization unit, performing:
Each final index in the intellectual property dimension parameters is obtained respectively;
if the type of the current final-stage index is of a maximum proportion type, the current final-stage index is directly used as a normalization parameter of the current final-stage index;
if the type of the current final-stage index is a minimum proportion type, taking the difference value between the 1 and the current final-stage index as a normalization parameter of the current final-stage index;
If the type of the current final-stage index is non-proportional, normalizing the same non-proportional final-stage index in each enterprise based on the data distribution condition of the same non-proportional final-stage index in all enterprises to obtain the normalized parameter of the current final-stage index;
And respectively replacing each final-stage index in the intellectual property dimension parameters of each enterprise with the normalization parameters of the corresponding final-stage index to obtain the intellectual property dimension normalization parameters of the corresponding enterprise.
Further, the boundary condition is at least one; each preset boundary condition includes: the final index corresponding to the boundary condition, the judgment rule of the boundary condition and the boundary regulation rule when the judgment rule is met;
In the boundary adjustment judging unit, for each enterprise, the following are performed: and respectively extracting the final-stage indexes corresponding to each boundary condition, judging whether the corresponding final-stage indexes meet the judging rules of the corresponding boundary conditions, and if so, acquiring the boundary regulating rules when the corresponding judging rules are met.
Further, the first-level index in the intellectual property dimension parameter comprises an index of a scientific creation result, an index of a patent quality, an index of continuous growth, an index of talent construction and an index of innovation and transformation.
Compared with the prior art, the invention has at least one of the following beneficial effects:
According to the enterprise intellectual property dimension review system provided by the invention, the database of the intellectual property dimension data retrieval platform is called to obtain the intellectual property dimension parameters of the enterprise on the intellectual property dimension data retrieval platform, so that the parameter data required by review can be obtained in real time.
Meanwhile, based on the acquired intellectual property dimension parameters of the enterprise, a primary review result of the intellectual property dimension of the enterprise is obtained; the primary evaluation result is subjected to distribution analysis, and the accuracy of the evaluation result is primarily judged by judging whether the deviation distribution of the primary evaluation result meets the preset distribution; when the accuracy is insufficient, namely the primary review result does not meet the preset distribution, correcting the primary review result through skewness adjustment, so that the accuracy of the review result is improved.
Corresponding deflection adjustment is respectively carried out on different deflection distributions, such as middle positive deflection, middle negative deflection, high positive deflection distribution and the like, so that objectivity in the evaluation process and transverse comparability of evaluation results are ensured, the efficiency of enterprise intellectual property dimension evaluation is effectively improved, and the method has high practical value.
In the invention, the technical schemes can be mutually combined to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, like reference numerals being used to designate like parts throughout the drawings;
FIG. 1 is a schematic diagram of an enterprise intellectual property dimension review system according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a primary review module according to an embodiment of the present invention.
Detailed Description
The following detailed description of preferred embodiments of the application is made in connection with the accompanying drawings, which form a part hereof, and together with the description of the embodiments of the application, are used to explain the principles of the application and are not intended to limit the scope of the application.
In one embodiment of the present invention, an enterprise intellectual property dimension review system is disclosed, and the system has a structure schematic shown in fig. 1, and includes:
The parameter acquisition module is used for acquiring intellectual property dimension parameters of enterprises on the intellectual property dimension data retrieval platform by calling a database of the intellectual property dimension data retrieval platform;
The primary review module is used for obtaining a primary review result of the intellectual property dimension of the enterprise based on the acquired intellectual property dimension parameter of the enterprise;
the distribution analysis module is used for carrying out distribution analysis on the primary review result to obtain the skewness distribution of the primary review result of the enterprise on the intellectual property dimension data retrieval platform; the skewness distribution is preset distribution or non-preset distribution;
The deviation adjusting module is used for performing deviation adjustment on the primary review result of the enterprise on the intellectual property dimension data retrieval platform when the deviation distribution is non-preset distribution;
The visual display module is used for visually displaying primary review results in preset distribution or review results after deviation adjustment in non-preset distribution.
The functions of the respective modules are described in detail as follows:
(1) Parameter acquisition module
In this embodiment, the parameter obtaining module may select a real-time or timing manner to obtain the intellectual property dimension parameters of the enterprise on the intellectual property dimension data retrieval platform according to the review period of the enterprise intellectual property dimension review system and the update condition of the intellectual property dimension parameters of the enterprise on the intellectual property dimension data retrieval platform. In addition, the parameter acquisition module in the embodiment can also respond to the enterprise intellectual property dimension review request of the user to acquire the intellectual property dimension parameters of the enterprise on the intellectual property dimension data retrieval platform, and start the working process of the subsequent module until the review result is visually displayed. It should be noted that, the intellectual property dimension data retrieval platform in this embodiment includes a patent retrieval platform and a non-patent retrieval platform (such as a trademark retrieval platform, an enterprise information query platform, etc.), and the intellectual property dimension parameters are obtained through a plurality of platforms.
In the implementation process, the content of the intellectual property dimension parameter can be preset in advance. Illustratively, the intellectual property dimension parameter may comprise several primary indicators, each of which is subdivided by several levels of secondary indicators. When the intellectual property dimension parameters of the enterprises on the intellectual property dimension data retrieval platform are required to be obtained, all final indexes in the intellectual property dimension parameters are directly obtained. To facilitate a better understanding of the implementation of this embodiment by those skilled in the art, this embodiment also presents an example form of intellectual property dimension parameters, as shown in table 1.
Table 1 example forms of intellectual property dimension parameters
In table 1, the first-level index in the intellectual property dimension parameter includes a scientific achievement index, a patent quality index, a continuous growth index, a talent construction index and an innovation transformation index. Each first-level index is subdivided into a second-level index, a third-level index and a fourth-level index to form a hierarchical structure diagram.
At this time, the four-level index is used as the final-level index. Specific details are described below:
1) Index of achievements of originality of science
The scientific achievements index is used for indicating the scientific achievements of the current enterprises in patent and non-patent aspects. That is, the data statistics analysis of the number of patents, non-patents (trademark, soft copy and standard) and the like, the right duty ratio and the like owned by the enterprise reflects the liveness and achievement of the originality of the enterprise. The index of the achievements of the origins of science includes two secondary indexes: patent condition indicators and non-patent condition indicators.
The patent condition index is used for indicating the current scientific achievement condition of the enterprise in patent. The enterprise patent profile is generally known by the total patent amount, patent availability, and coverage of the patent for that enterprise. The patent condition indexes comprise six three-level indexes: general patent condition index, effective patent condition index, invalid patent condition index, invention patent condition index, technical field condition index and high-value patent condition index.
The patent overall situation index includes a four-level index: total amount of patent. The total amount of patents is used to indicate the total amount of patents currently filed by the corporation. I.e., the total number of inventions, new and appearance patents currently filed by the corporation.
The effective patent condition index includes a four-level index: the effective patent ratio. The effective patent ratio is used to indicate the ratio of the number of effective patents to the total number of patents in the current enterprise.
The invalid patent condition index includes a four-level index: invalid patent duty cycle. The invalid patent ratio is used for indicating the proportion of the number of invalid patents in the current enterprise to the total patent amount. It should be noted that the sum of the effective patent ratio and the ineffective patent ratio is not 100%, because the enterprise is still partially under examination.
The inventive patent condition index comprises a four-level index: the invention patent ratio. Inventive patent ratio is used to indicate the ratio of the number of inventive patents to the total number of patents in the current business.
The technical field condition index comprises a four-level index: and (5) covering the technical field. Technical field coverage is used to indicate the number of subclasses covered by all patents of the current enterprise.
The high value patent situation index includes two four indices: high value patent quantity and high value patent ratio. Wherein the number of high-value patents is used to indicate the number of high-value patents of the current enterprise. The high-value patent proportion is used for indicating the proportion of the number of high-value patents in the current enterprise to the total patent amount.
The non-patent condition index is used for indicating the current scientific achievement condition of the enterprise in patent. I.e., a non-patent overview of the business in the field of intellectual property. The non-patent condition indexes comprise four three-level indexes: trademark condition index, soft and big condition index, work condition index and standard condition index.
Wherein,
The trademark condition index includes a four-level index: number of trademarks. I.e., the number of brands currently owned by the business.
The soft-case index includes a four-level index: soft-written number. I.e., the number of books that are currently owned by the business.
The work condition index includes a four-level index: number of works. I.e., the number of works currently owned by the enterprise.
The standard condition index includes a four-level index: standard quantity. I.e., the standard quantity currently owned by the business.
2) Quality index of patent
The patent quality index is used for indicating the overall quality condition of the current enterprise in patent aspect. That is, the patent quality index is an evaluation dimension for quantitatively analyzing the patent quality of the enterprise by deep mining of all the patents held by the enterprise. The patent quality index comprises five secondary indexes: patent same family condition index, patent mortgage condition index, war industry new industry condition index, patent maintenance year index and patent winning condition index. Wherein,
The patent family condition index is used for indicating the patent family condition of the current enterprise. I.e. the covered national case of the patent. The patent family condition indexes comprise two three-level indexes: covering national condition indexes and overseas patent condition indexes. Wherein, the coverage country situation index includes a four-level index: covering the national total. The total number of covered countries is used to indicate the number of countries covered by the current enterprise family patent. The overseas patent family condition indexes comprise two four-level indexes: the proportion of patents possessing overseas aliases and the average overseas aliases. The proportion of the overseas patent family is used for indicating the proportion of the overseas patent family owned by the current enterprise to the total patent. The average overseas sibling number is used to indicate the number of overseas siblings currently owned by the enterprise.
And the patent operation condition index is used for indicating the patent mortgage condition of the current enterprise. The occurrence of patent right mortgage behavior means that the market value of this patent is somewhat approved. The patent mortgage condition index comprises a three-level index: and (5) a patent mortgage condition index. The patent operation condition index comprises a four-level index: total number of mortgages. The total number of mortgages is used to indicate the total number of mortgages of the current enterprise patent.
The industrial development condition index is used for indicating the patent condition of the current enterprise belonging to the strategic emerging industry. The strategic emerging industry represents both the direction of technological innovation and the direction of industry development. The industrial development condition index comprises a three-level index: and (5) a war industry and new industry condition index. The war industry new production condition index comprises a four-level index: the proportion of patents in war industry and new industry. The war new industry patent proportion is used for indicating the proportion of patents belonging to the strategic emerging industry of the current enterprise to the total patent amount.
The patent maintenance age index is used for indicating the current patent maintenance age condition of enterprises. Patent maintenance refers to the process by which patentees pay a prescribed number of maintenance fees to patent authorities for patent to continue to be effective during patent statutory protection. The maintenance years represent the importance of the patent to some extent. The patent maintenance age index includes two three levels of index: remaining expiration date and maintenance age condition indicators. Wherein the remaining validity period condition index includes a four-level index: average remaining validity period. The average remaining validity period is used for indicating the average remaining validity period of the current enterprise patent. The maintenance age condition indicator includes a four-level indicator: average maintenance years. Average maintenance years, which are used to indicate the average maintenance years of current business patents.
The patent honor condition index is used for indicating the patent winning condition of the current enterprise. The patent honor condition index comprises a three-level index: a patent prize winning condition index. The patent prize index includes a four-level index: number of patent winnings. The number of patent winnings is used for indicating the number of patent Chinese patent winnings or local winnings.
3) Continuous growth index
And the continuous growth index is used for indicating the continuous growth condition of the current enterprise in innovation. The continuous growth force is analyzed from the aspects of enterprise innovation dynamics and enterprise history. The growth condition of the enterprise patent is reflected by carrying out statistical analysis on the data such as the year of patent application, the overall score condition of the patent, the times of obstetrical and academic research and the like of the enterprise. The sustained growth index includes five secondary indexes: innovative dynamic situation index, innovation team scale index, innovation quality situation index, obstetrical and academic research collaboration situation index and technical introduction situation index. Wherein,
The innovation dynamic condition index is used for indicating the innovation dynamic condition of the current enterprise. The innovation dynamic condition index is described by two aspects of innovation history and innovation vitality of an enterprise. The innovative dynamic condition index includes two three levels of index: an innovation history index and an innovation vitality index. Wherein, the innovation history index comprises a four-level index: a history of innovations. An innovation history indicating the total number of years the business applied for patent. The innovation vitality index comprises two four-level indexes: innovation liveness in the last ten years and innovation proportion in the last five years. Among them, innovation activity in the last decade is used to indicate the total number of patented years in the last decade. The innovation specific gravity of the last five years is used to indicate the ratio of the number of inventions of the last five years to the total number of inventions.
And the innovation team scale index is used for indicating the conditions of the enterprise inventors. The innovation team scale index includes a three-level index: the inventors' situation index. The inventor condition index includes two four-level indexes: average number of inventors and total number of inventors.
The innovation quality condition index is used for indicating the innovation quality condition of the patent of the current enterprise. Innovative quality case indicators represent the overall case of a patent from the enterprise patent dimension. The innovation quality condition index comprises a three-level index: a patent value scoring index. The patent value scoring index includes two four levels of indices: average patent score and highest patent score. Wherein the average patent score is used to indicate the average of all patent scores of the current business. The highest patent score is used to indicate the highest patent score of the current business.
The patent application condition index is used for indicating the condition of the current enterprise in the aspect of obstetric research and study. The obstetric research work is the butt joint and coupling of the upstream, middle and downstream of the technical innovation, which is beneficial to improving the innovation capability of enterprises. The patent application condition index comprises a three-level index: the obstetrics and academic research is done with index of the condition. The index of the obstetrical research situation comprises a four-level index: the number of times of obstetric and academic research. The times of the obstetric study are used for indicating the times of the enterprise to develop the obstetric study.
The technology acquisition path index is used for indicating the condition of the current enterprise technology introduction. The technological acquisition approach index analyzes the innovative dynamics of the enterprise under the condition that the enterprise is shifted into a patent. The technical introduction condition index comprises a three-level index: the technology introduces condition indexes. The technical introduction condition index comprises a four-level index: the technology introduces proportions. The technical introduction ratio is used for indicating the proportion of patents transferred into enterprises.
4) Talent construction index
Talent construction indexes are used for indicating the quantity and quality conditions of the inventors of the current enterprise. The talent construction index quantitatively reflects the overall strength of the enterprise in terms of talent reserves by carrying out mining analysis on the quantity and the quality of the enterprise inventors. Talent construction indexes comprise a secondary index: and (5) innovating a team scale index. The innovation team scale index includes a three-level index: the inventors' situation index. The inventor condition index includes two four-level indexes: average number of inventors and total number of inventors. Wherein the average number of inventors is used to indicate the average number of inventors of all patent applications of the current enterprise. The total number of inventors is used to indicate the total number of inventors of all patent applications currently.
5) Innovative conversion index
The innovation transformation index is used for indicating the innovation transformation condition of the current enterprise. The innovative transformation index refers to deep excavation of the conditions of transferring, licensing, customs filing and the like of the enterprise patent, so that the integral transformation condition of the enterprise patent is reflected. The innovative conversion index comprises three secondary indexes: patent transfer case index, patent permit case index, and patent customs filing case index. Wherein,
The patent transfer case index includes a three-level index: index of number of patent transfer. Patent transfer is a legal act for patent application and patent owners to grant patent application and patent rights to others. The patent transfer number index includes a four-level index: number of patent transfers.
The patent licensing index includes a three-level index: and (5) a patent permission number index. Patent licensing refers to licensing proprietary technology to others, allowing licensees to implement their proprietary technology in a certain time and region and collecting a certain patent licensing fee. The patent permission index includes a four-level index: number of patent permissions.
The patent customs clearance condition index comprises a three-level index: patent customs records condition index. Patent customs clearance: the intellectual property right person registers the intellectual property condition of the intellectual property right person in a customs countersign in a written form so that the customs can actively protect the related intellectual property in the process of supervising import and export goods. The patent customs clearance condition index comprises a four-level index: the patent customs records times.
(2) Primary review module
The primary review module comprises a parameter normalization unit, an operation unit, a boundary adjustment judging unit and a boundary adjustment unit, and the structural schematic diagram is shown in fig. 2. Wherein,
1) Parameter normalization unit
And the parameter normalization unit is used for carrying out normalization processing on the intellectual property dimension parameters to obtain the intellectual property dimension normalization parameters of each enterprise.
In this embodiment, the type of the final stage index is a proportional type or a non-proportional type, and the proportional type is a maximum proportional type or a minimum proportional type;
in the parameter normalization unit, performing:
Step S1: each final index in the intellectual property dimension parameters is obtained respectively;
step S2: respectively obtaining normalization parameters of the corresponding final stage indexes according to the type of each final stage index; specifically:
a) And if the type of the current final-stage index is in a maximum proportion type, the current final-stage index is directly used as a normalization parameter of the current final-stage index.
B) And if the type of the current final-stage index is an extremely small proportion type, taking the difference value between 1 and the current final-stage index as a normalization parameter of the current final-stage index.
C) If the type of the current final-stage index is non-proportional, normalizing the same non-proportional final-stage index in each enterprise based on the data distribution condition of the same non-proportional final-stage index in all enterprises to obtain the normalized parameters of the current final-stage index.
Examples of types of final metrics in the intellectual property dimension parameters are shown in table 2.
TABLE 2 type examples of final metrics in intellectual Property dimension parameters
It should be emphasized that in the present embodiment, the non-proportional type is a very large non-proportional type or an intermediate non-proportional type.
And carrying out normalization processing on the final-stage index with the maximum non-proportion type by adopting an Ln normalization processing algorithm, namely: logarithmic transformation ln (Xi)/ln (Xmax), xi representing the actual value of the corresponding final-stage index, xmax representing the maximum value of the final-stage index of the same maximum non-proportional type of the corresponding final-stage index in all enterprises.
For the intermediate non-proportional type final stage index, dividing the intermediate non-proportional type final stage index into odd intervals according to the data distribution of the corresponding intermediate non-proportional type final stage index; the normalization parameter of the final index falling into the middle interval is 1; the normalization parameters of the final-stage indexes falling into the forward and backward intervals of the middle interval are sequentially decreased, and the normalization parameters of the current final-stage indexes are obtained. Illustratively, the data distribution of the existing average remaining validity period is analyzed, e.g. divided into 11 intervals. And the normalization parameter of the final stage index corresponding to the 6 th interval is 1, and the forward and backward final stage indexes are respectively and sequentially decreased by 0.2.
Step S3: and respectively replacing each final-stage index in the intellectual property dimension parameters of each enterprise with the normalization parameters of the corresponding final-stage index to obtain the intellectual property dimension normalization parameters of the corresponding enterprise.
2) Arithmetic unit
And the operation unit is used for operating the intellectual property dimension normalization parameters to obtain a first review result of the intellectual property dimension of each enterprise.
In the operation unit, a mode of combining the analytic hierarchy process and the entropy weight process to realize the intellectual property dimension normalization parameter operation is provided. The specific description is as follows:
and respectively determining the first weights of the indexes of each level by using an analytic hierarchy process. In the specific implementation process, expert opinions are combined in advance, and a 1-9 scale method is adopted to compare the importance of each index of the same level (hierarchy) so as to obtain a first weight of each level of index.
And determining the second weight of each level of index by using an entropy weight method.
Combining the first weight and the second weight of each level of index to obtain the comprehensive weight of each level of index; the combination of the first weight and the second weight may be determined according to circumstances, and is not limited herein.
And performing step-by-step operation from the last stage to the first stage by utilizing the comprehensive weight of each stage of index and each intellectual property dimension normalization parameter to finally obtain a first review result of the intellectual property dimension of the corresponding enterprise.
That is, for each enterprise, a corresponding primary review result is obtained by performing the following operations:
Firstly, carrying out weighted summation on normalization parameters of each four-level index data and corresponding comprehensive weights thereof, and calculating to obtain the numerical value of the corresponding three-level index. And then, carrying out weighted summation on the normalization parameters of each three-level index and the corresponding comprehensive weights thereof, and calculating to obtain the numerical value of the corresponding two-level index. And then, carrying out weighted summation on the numerical values of the secondary indexes and the corresponding comprehensive weights thereof, and calculating to obtain the numerical value of the corresponding primary index. And finally, carrying out weighted summation on the numerical values of the first-level indexes and the corresponding comprehensive weights of the first-level indexes, and calculating to obtain a first review result of the intellectual property dimension of the corresponding enterprise.
3) Boundary adjustment judging unit
The boundary adjustment judging unit is used for respectively comparing the intellectual property dimension parameter of each enterprise with a preset boundary condition and judging whether the corresponding enterprise needs boundary adjustment or not; if the judgment result is that the corresponding enterprise does not need to carry out boundary adjustment, the first review result of the intellectual property dimension of the corresponding enterprise is directly used as the primary review result of the intellectual property dimension of the corresponding enterprise.
In the actual process, the judgment result of the boundary adjustment judgment unit also has the condition that the corresponding enterprise needs to carry out boundary adjustment. Therefore, the boundary adjustment judging unit is further configured to generate a boundary adjustment rule of the corresponding enterprise if the judging result indicates that the corresponding enterprise needs to perform boundary adjustment. At this time, the primary review module also needs to include a boundary adjusting unit.
The boundary condition is at least one; each preset boundary condition includes: the final index corresponding to the boundary condition, the judgment rule of the boundary condition and the boundary regulation rule when the judgment rule is met;
in the boundary adjustment judging unit, for each enterprise, the following are performed:
And respectively extracting the final-stage indexes corresponding to each boundary condition, judging whether the corresponding final-stage indexes meet the judging rules of the corresponding boundary conditions, and if so, acquiring the boundary regulating rules when the corresponding judging rules are met.
4) Boundary adjusting unit
The boundary adjusting unit is used for carrying out boundary adjustment on the first review result of the intellectual property dimension of the corresponding enterprise according to the boundary adjusting rule of the corresponding enterprise; and the result of the first review result of the intellectual property dimension of the corresponding enterprise after the boundary adjustment is used as a primary review result of the intellectual property dimension of the corresponding enterprise.
Illustratively, in the present embodiment, the following boundary conditions may be set:
boundary condition 1:
The final index corresponding to the boundary condition: an invalid patent duty cycle;
The judgment rule of the boundary condition: whether the invalid patent duty cycle is equal to 1;
boundary adjustment rules when the judgment rules (invalid patent duty ratio equal to 1) are satisfied: first review result x 0.1 of intellectual property dimension of corresponding enterprise;
Boundary condition 2:
the final index corresponding to the boundary condition: the effective patent duty cycle;
The judgment rule of the boundary condition: whether the effective patent duty cycle is equal to 0;
Boundary adjustment rules when the judgment rules (effective patent duty ratio equal to 0) are satisfied: first review result x 0.1 of intellectual property dimension of corresponding enterprise;
Boundary condition 3:
the final index corresponding to the boundary condition: inventive patent duty cycle
The judgment rule of the boundary condition: the invention patent is whether the duty ratio is 0;
Boundary adjustment rules when the judgment rules (inventive patent duty ratio is equal to 0) are satisfied: the first review result of intellectual property dimension of the corresponding business x 0.6.
In the implementation process, a related clamping relationship between boundary conditions can be set, for example, the boundary condition 1 is judged first, the boundary condition 2 is judged when the boundary condition 1 is not met, the boundary condition 3 is judged when the boundary condition 2 is not met, and the boundary adjustment is performed on the first evaluation result of the intellectual property dimension of the corresponding enterprise according to the judgment result.
(3) Distribution analysis module
As the primary review results of the intellectual property dimension of the enterprise on the platform rarely follow the preset distribution, the skewness distribution can well measure the asymmetry of the data distribution, and is very important for knowing the macroscopic skewness distribution condition of the enterprise. Meanwhile, the skewness distribution can reveal the distribution situation of most enterprises, and simultaneously reflects the size relation among the enterprise mean value, the median and the mode. Therefore, the present embodiment makes statistics of the degree of asymmetry of the data distribution by introducing the concept of skewness distribution.
In the distribution analysis module, the bias distribution S of the primary review results of the enterprise on the intellectual property dimension data retrieval platform is obtained according to the following formula:
Wherein N represents the total number of enterprises on the intellectual property dimension data retrieval platform, P n represents the primary review result of the nth enterprise on the intellectual property dimension data retrieval platform, and mu and sigma respectively represent the mean value and standard deviation of the primary review results of all enterprises on the intellectual property dimension data retrieval platform.
Different skewness distributions mean different degrees of deviation of the data distribution from the preset distribution, requiring adjustment using different transformations. In this embodiment, when the value range of the skewness distribution is between [ -a, a ], the skewness distribution is a preset distribution, a is a positive number smaller than 1, and a may be 0.5 plus or minus 0.1 or 0.05, for example. Otherwise, the skewness distribution is a non-preset distribution. The types of the non-preset distribution comprise middle positive deflection, middle negative deflection, high positive deflection or high negative deflection distribution, and corresponding deflection adjustment is performed based on the non-preset distribution of different types.
Illustratively, in this embodiment, a has a value of 0.5, and the bias distribution is divided into five levels according to practical experience, and the specific grading criteria are shown in table 3:
TABLE 3 grading criteria for skewness distribution
| Enterprise skewness classification | Deviation value of whole enterprise |
| Preset distribution (e.g. symmetrical) | -0.5 To 0.5 |
| Moderate positive/negative bias | 0.5 To 1.0 and-0.5 to-1.0 |
| High positive/negative bias | 1.0 And < -1.0 |
The analysis table 3 shows that when the value range of the skewness distribution is between [ -0.5,0.5], the skewness distribution is a preset distribution; otherwise, the skewness distribution is a non-preset distribution. When the value range of the deflection distribution is between (0.5, 1), the deflection distribution is a medium positive deflection distribution, and when the value range of the deflection distribution is between (minus 1, -0.5), the deflection distribution is a medium negative deflection distribution; when the value of the skewness distribution is larger than 1, the skewness distribution is highly positive skewness distribution; when the value of the skewness distribution is smaller than-1, the skewness distribution is high negative skewness distribution.
(4) Deflection adjusting module
In the skewness adjustment module, when the skewness distribution is a moderate positive skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (2):
Wherein P n' represents the evaluation result of the nth enterprise after the bias adjustment;
when the skewness distribution is a moderate negative skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (3):
wherein P MAX represents the maximum value of primary review results in all enterprises on the intellectual property dimension data retrieval platform;
when the skewness distribution is high positive skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (4):
Pn′＝k1*lnPn (4)
Wherein k 1 represents a height positive bias adjustment coefficient;
When the skewness distribution is high negative skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (5):
Pn′＝k2*ln(PMAX-Pn) (5)
Where k 2 denotes a high negative bias adjustment coefficient.
(5) Visual display module
After the primary review result in the preset distribution or the review result after the bias adjustment in the non-preset distribution is obtained, the corresponding review result can be visually displayed.
The form of visual presentation includes, but is not limited to, forms of tables, graphs, curves, and the like. In addition, the visual display of the review results of the selected part of enterprises can be selected, so that the diversity of display modes is enriched.
In summary, in the enterprise intellectual property dimension review system provided by the embodiment, the intellectual property dimension parameters of the enterprise on the intellectual property dimension data retrieval platform are obtained by calling the database of the intellectual property dimension data retrieval platform, so that the parameter data required for review can be obtained in real time. Meanwhile, based on the acquired intellectual property dimension parameters of the enterprise, a primary review result of the intellectual property dimension of the enterprise is obtained; and the distribution analysis is carried out on the primary review results so as to correct the distribution situation of the primary review results according to the bias distribution, thereby ensuring the objectivity in the review process and the transverse comparability of the review results, effectively improving the efficiency of enterprise intellectual property dimension review and having high practical value.
Those skilled in the art will appreciate that all or part of the flow of the methods of the embodiments described above may be accomplished by way of a computer program to instruct associated hardware, where the program may be stored on a computer readable storage medium. Wherein the computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, etc.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention.
Claims (6)
1. An enterprise intellectual property dimension review system, comprising:
The parameter acquisition module is used for acquiring intellectual property dimension parameters of enterprises on the intellectual property dimension data retrieval platform by calling a database of the intellectual property dimension data retrieval platform;
The primary review module is used for obtaining a primary review result of the intellectual property dimension of the enterprise based on the acquired intellectual property dimension parameter of the enterprise;
the distribution analysis module is used for carrying out distribution analysis on the primary review result to obtain the skewness distribution of the primary review result of the enterprise on the intellectual property dimension data retrieval platform; the skewness distribution is preset distribution or non-preset distribution;
The deviation adjusting module is used for performing deviation adjustment on the primary review result of the enterprise on the intellectual property dimension data retrieval platform when the deviation distribution is non-preset distribution;
The visual display module is used for visually displaying primary review results in preset distribution or review results after deviation adjustment in non-preset distribution;
the distribution analysis module acquires the bias distribution S of the primary review result of the enterprise on the intellectual property dimension data retrieval platform according to the following formula:
Wherein N represents the total number of enterprises on the intellectual property dimension data retrieval platform, P n represents the primary review result of the nth enterprise on the intellectual property dimension data retrieval platform, and mu and sigma respectively represent the mean value and standard deviation of the primary review results of all enterprises on the intellectual property dimension data retrieval platform;
When the value range of the skewness distribution is between [ -a, a ], the skewness distribution is preset distribution, and a is a positive number smaller than 1; otherwise, the skewness distribution is non-preset distribution;
The types of the non-preset distribution comprise middle positive deflection, middle negative deflection, high positive deflection or high negative deflection distribution, and corresponding deflection adjustment is performed based on the non-preset distribution of different types;
In the deflection-degree adjusting module,
When the skewness distribution is a moderate positive skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (2):
Wherein P n' represents the evaluation result of the nth enterprise after the bias adjustment;
when the skewness distribution is a moderate negative skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (3):
wherein P MAX represents the maximum value of primary review results in all enterprises on the intellectual property dimension data retrieval platform;
when the skewness distribution is high positive skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (4):
Pn′＝k1*lnPn(4)
Wherein k 1 represents a height positive bias adjustment coefficient;
When the skewness distribution is high negative skewness distribution, carrying out skewness adjustment on the primary evaluation result of the enterprise on the intellectual property dimension data retrieval platform according to a formula (5):
Pn′＝k2*ln(PMAX-Pn)(5)
Where k 2 denotes a high negative bias adjustment coefficient.
2. The enterprise intellectual property dimension review system of claim 1, wherein the primary review module comprises:
the parameter normalization unit is used for carrying out normalization processing on the intellectual property dimension parameters to obtain the intellectual property dimension normalization parameters of each enterprise;
the operation unit is used for operating the intellectual property dimension normalization parameters to obtain a first review result of the intellectual property dimension of each enterprise;
The boundary adjustment judging unit is used for respectively comparing the intellectual property dimension parameter of each enterprise with a preset boundary condition and judging whether the corresponding enterprise needs boundary adjustment or not; if the judgment result is that the corresponding enterprise does not need to carry out boundary adjustment, the first review result of the intellectual property dimension of the corresponding enterprise is directly used as the primary review result of the intellectual property dimension of the corresponding enterprise.
3. The enterprise intellectual property dimension review system of claim 2, wherein the primary review module further comprises a boundary adjustment element;
The boundary adjustment judging unit is further configured to generate a boundary adjustment rule of the corresponding enterprise if the judging result indicates that the corresponding enterprise needs to perform boundary adjustment;
The boundary adjusting unit is used for carrying out boundary adjustment on the first review result of the intellectual property dimension of the corresponding enterprise according to the boundary adjusting rule of the corresponding enterprise; and the result of the first review result of the intellectual property dimension of the corresponding enterprise after the boundary adjustment is used as a primary review result of the intellectual property dimension of the corresponding enterprise.
4. The enterprise intellectual property dimension review system of claim 3, wherein the intellectual property dimension parameter comprises a plurality of primary indicators, each primary indicator being subdivided into a plurality of levels of subordinate indicators, wherein the type of the final indicator is proportional or non-proportional, and the proportional is either a very large scale or a very small scale;
in the parameter normalization unit, performing:
Each final index in the intellectual property dimension parameters is obtained respectively;
if the type of the current final-stage index is of a maximum proportion type, the current final-stage index is directly used as a normalization parameter of the current final-stage index;
if the type of the current final-stage index is a minimum proportion type, taking the difference value between the 1 and the current final-stage index as a normalization parameter of the current final-stage index;
If the type of the current final-stage index is non-proportional, normalizing the same non-proportional final-stage index in each enterprise based on the data distribution condition of the same non-proportional final-stage index in all enterprises to obtain the normalized parameter of the current final-stage index;
And respectively replacing each final-stage index in the intellectual property dimension parameters of each enterprise with the normalization parameters of the corresponding final-stage index to obtain the intellectual property dimension normalization parameters of the corresponding enterprise.
5. The enterprise intellectual property dimension review system of claim 4, wherein the boundary condition is at least one; each preset boundary condition includes: the final index corresponding to the boundary condition, the judgment rule of the boundary condition and the boundary regulation rule when the judgment rule is met;
In the boundary adjustment judging unit, for each enterprise, the following are performed: and respectively extracting the final-stage indexes corresponding to each boundary condition, judging whether the corresponding final-stage indexes meet the judging rules of the corresponding boundary conditions, and if so, acquiring the boundary regulating rules when the corresponding judging rules are met.
6. The system of claim 4, wherein the first level indicators in the intellectual property dimension parameters include a scientific achievement indicator, a patent quality indicator, a sustained growth indicator, a talent construction indicator, and an innovation transformation indicator.
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