Method, device and storage medium for generating data element based on digital spectrum

Abstract

The present invention discloses a method, device and storage medium for generating data elements based on digital spectrum. The method converts all the data to be managed into corresponding digital signals and further converts them into digital spectrum. The digital spectrum is set so that it can characterize the change frequency and change amplitude of data information, as well as the similarity and correlation between data information. Then, based on the digital spectrum, data element characteristics are extracted and data elements are generated. The data elements are used to replace the original data, so that the characteristics of data information can be characterized by data elements during the circulation of data elements, thereby effectively reducing the risk of data privacy leakage, thereby improving data utilization, and ultimately greatly improving user experience.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device and storage medium for generating data elements based on digital spectrum. Background Art

[0002] As communication technology becomes more and more advanced, people are paying more and more attention to the protection of personal privacy and data related to life, work, etc. At present, these data are usually provided to applications through privacy calculation or desensitization. However, whether it is privacy calculation or sending after desensitization, the data still needs to be provided to the application party in the end. Since the data content and sensitive information are not easy to control, this processing method still has certain security risks. Therefore, how to use it effectively while effectively ensuring data security has become a problem that needs to be solved urgently. Summary of the invention

[0003] The present invention provides a method, device and storage medium for generating data elements based on digital spectrum, so as to solve the problem that data cannot be used under the condition of effectively ensuring data security.

[0004] In a first aspect, the present invention provides a method for generating data elements based on a digital spectrum, the method comprising: acquiring data to be governed, and converting the data to be governed into corresponding digital signals according to data information in the data to be governed, wherein the data to be governed is data that can be traded, circulated and used after being allowed to be governed accordingly; clustering and sorting the digital signals according to the change frequency and change amplitude of use of each data information in the data to be governed, and the similarity and correlation relationship between the data information, and converting the digital signals into a digital spectrum, so as to characterize the change frequency and change amplitude of each data information in the data to be governed, and the similarity and correlation relationship between the data information through the digital spectrum; extracting data element features from the digital spectrum through a preset data element model, and generating data elements based on the data element features, so as to replace the original data for data trading, circulation and use through the data elements.

[0005] Optionally, the acquiring the data to be governed includes: receiving a request from a user to generate a data element, and acquiring corresponding data to be governed according to the request, wherein the request includes information of the data to be governed required to generate the data element.

[0006] Optionally, converting the data to be governed into a corresponding digital signal according to data information in the data to be governed includes: converting all data information in the data to be governed into corresponding value fields according to a preset conversion principle to obtain a digital signal corresponding to the data to be governed.

[0007] Optionally, clustering and sorting the digital signals according to the usage change frequency and change range of each data information in the data to be governed, and the similarity and correlation between the data information, and converting the digital signals into digital spectrums, including: setting the data whose change frequency of the data information in the data to be governed is lower than a preset change frequency threshold as the data of the core field with basic characteristics;

[0008] The data whose similarity between the name field of the data information to be managed and the content corresponding thereto is greater than a preset similarity threshold is set as data of the quality field having similarity characteristics;

[0009] The data whose correlation between data information in the data to be managed is set to be data of an energy field with correlation characteristics, if the correlation between data information is greater than a preset correlation threshold;

[0010] The data signals are clustered and sorted based on the dimensions of change frequency, change amplitude, and the similarity and correlation between the data information, and converted into corresponding digital spectra.

[0011] Optionally, the step of setting the data whose change frequency of data information in the data to be governed is lower than a preset change frequency threshold as data of a core field having basic characteristics includes:

[0012] The change frequency of each data information in the data to be managed within a preset time period is obtained, and the data information with a change frequency lower than the preset change frequency threshold is set as the data of the core field with basic characteristics.

[0013] Optionally, the method also includes: the digital spectrum represents the change frequency, change amplitude, and similarity and correlation between each data in the data to be managed through the width, height and sorting position of each value field in the digital signal.

[0014] Optionally, the method further comprises: Calculate the data value of the data element, where f(n,W) represents the maximum value obtained when the amount of information of the data to be governed is W among the first n data element features, and wn and vn represent the value and amount of information of the nth data element feature, respectively; measure the value of the data element circulating in the data market based on the calculated data value of the data element, so as to realize the circulation and use of the data element in the data market.

[0015] Optionally, extracting data element features from the digital spectrum by using a preset data element model and generating data elements based on the data element features comprises: extracting data element features from the digital spectrum by using a preset dynamic programming algorithm and generating data elements based on the data element features, wherein the data element features include the same feature attributes and different feature attributes between the digital spectra of different data to be managed; the preset dynamic programming algorithm is ; Set the data element characteristics to X1, X2, ..., X k , under each data component feature, the attributes and values ​​of the digital spectrum of different data to be managed are different. Let the value of the jth attribute of the data component feature X1 of the i-th data to be managed be X 1ij , where i, j and k are all natural numbers, and n is the number of data element features. is the numerical difference between the data element characteristics, which is obtained by taking the data element characteristic of the i-th data to be managed as a benchmark and comparing the data element characteristics of other data to be managed with the benchmark data element characteristics.

[0016] In a second aspect, the present invention provides a device for generating data elements based on a digital spectrum, the device comprising: an acquisition unit, used to acquire data to be governed, and convert the data to be governed into corresponding digital signals according to data information in the data to be governed, wherein the data to be governed is data that can be traded, circulated and used after being allowed to be governed accordingly; a first processing unit, used to cluster and sort the digital signals according to the frequency and magnitude of changes in the use of each data information in the data to be governed, and the similarity and correlation between the data information, and convert the digital signals into a digital spectrum, so as to characterize the frequency and magnitude of changes in each data information in the data to be governed, and the similarity and correlation between the data information through the digital spectrum; a second processing unit, used to extract data element features from the digital spectrum through a preset data element model, and generate data elements based on the data element features, so as to replace the original data for data trading, circulation and use through the data elements.

[0017] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements any of the above-mentioned methods for generating a data element based on a digital spectrum.

[0018] The beneficial effects of the present invention are as follows:

[0019] The present invention provides a method, device and storage medium for generating data elements based on digital spectrum. Specifically, the present invention converts all the data to be governed into corresponding digital signals, and further converts them into digital spectrum. The digital spectrum is set so that it can characterize the change frequency and change amplitude of each data information in the data to be governed, as well as the similarity and correlation between the data information. Then, based on the digital spectrum, the data element characteristics are extracted and the data element is generated. The data element is used to replace the original data, so that the data elements can be used to characterize the characteristics of the data during the circulation of data elements, thereby effectively reducing the risk of data privacy leakage, thereby improving data utilization, and ultimately greatly improving user experience.

[0020] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0022] Figure 1 It is a flowchart of a method for generating data elements based on a digital spectrum provided by an embodiment of the present invention;

[0023] Figure 2 It is a flow chart of a device for generating data elements based on digital spectrum provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not limit the present invention.

[0025] No matter whether data is sent through privacy computing or desensitization, the actual data must be provided to the application party in the form of data. After the data is provided to others, there will definitely be security risks because the data content and sensitive information are not easy to control. In addition, since the data is processed, it will also affect the data accuracy and flexibility when using the data to a certain extent. Therefore, how to achieve flexible use of data while ensuring data security has become an urgent problem that needs to be solved.

[0026] In order to solve the above problems, an embodiment of the present invention provides a method for generating data elements based on digital spectrum. The method of the present invention generates the data to be governed as data elements, which is equivalent to anonymizing the data, thereby playing a good role in data protection.

[0027] It should be noted that the collection and acquisition of various data in the present invention complies with relevant legal provisions and is authorized by the data provider. Any organization or individual that needs to obtain external data shall obtain authorization in accordance with the law and ensure data security, and shall not illegally collect, use, process, or transmit unauthorized or unprotected data, or illegally buy, sell, provide, or disclose unauthorized or unprotected data.

[0028] For specific implementation, see Figure 1 , the method described in the embodiment of the present invention includes:

[0029] S101. Obtaining data to be managed;

[0030] In specific implementation, the data to be governed in the embodiment of the present invention refers to data that can be traded, circulated and used after corresponding data processing. The method for generating data elements based on digital spectrum described in the embodiment of the present invention is a data governance technology. For example, the data to be governed in the embodiment of the present invention may be educational and scientific research data, and the educational and scientific research data may further include various specific data information such as faculty information, student status information, student payment data, academic and professional information, college diploma information, professional title information and professional qualification information. Of course, the above data can be anonymized and fuzzified, and may not point to a specific individual. The specific technical personnel in this field can arbitrarily set various specific data information under the data to be governed according to actual needs, and can also further set corresponding branch data information under each data information, such as further setting the faculty age, gender, teaching age, subject, etc. under the faculty information. The present invention does not make specific limitations on this. That is, in the embodiment of the present invention, the data to be governed may include multiple, and each data to be governed may further include multiple data information, and each data information may further include multiple branch data information.

[0031] Specifically, the embodiment of the present invention obtains the data to be governed according to the requirements of the data elements to be generated, and realizes the safe and flexible data transaction, circulation and use of the data to be governed after data processing of the data to be governed. That is, in the embodiment of the present invention, the user can select the data to generate the data element and the scope of the data to be governed according to his or her actual needs. For example, the student information and student payment data of a certain school can be selected to process and generate the data element, wherein the students of the above-mentioned certain school are the scope of the selected data to be governed, and then each student is a data to be governed, and the student information and student payment data are the specific data information in the selected data to be governed. Through this setting method of selecting the data to be governed on demand, the present invention can minimize the occupation of resources caused by the generation of data elements while ensuring that the user's use needs are met, thereby maximizing the user experience;

[0032] In a specific implementation, the user can directly select the specific required data to be managed from the client interface by directly linking to the server (the server is a server for generating data elements) on a preset display interface, such as through a client on the user side, and of course, by downloading a preset file from the server, such as the preset file can be various document forms, etc., and by selecting the required data to be managed in the downloaded form, and then feeding it back to the server for generating data elements, thereby collecting the data to be managed according to the user's needs. Of course, the user side can also directly edit and trigger a request to generate a data element, and the request includes the scope of the data to be managed and the required specific data information, and then the server parses the request and obtains the required data to be managed. The specific implementation method can be set and implemented by those skilled in the art according to actual needs, and the present invention does not specifically limit this;

[0033] For example, the present invention may be a request for receiving a user to generate a data element, wherein the request includes the scope of the data to be governed and the required data information, that is, the request may set which specific data is involved in the data, and then collect the data according to the request. In other words, since the specific content of the branch data information in different data to be governed is diverse, in the specific implementation, the user can select the specific branch data information involved in each data information according to actual needs, that is, the required branch data information can be selected from a certain data information, such as only selecting faculty information of a certain gender in faculty information, etc., which can be specifically set according to actual needs. Through the above settings, the present invention enables users to generate data elements in a targeted manner, so that the generated data elements can meet various usage requirements of subsequent data analysis.

[0034] In addition, it should be noted that the above description is only based on the example of a server. In specific implementation, users can also directly collect the required data on their own various terminals and generate data elements. That is, the embodiment of the present invention can generate data elements through a user's terminal or by setting up a dedicated server. Of course, for security reasons, the device that generates data elements must be a device that can effectively ensure data security.

[0035] In general, the embodiments of the present invention can determine the scope of the data to be governed and the data information to be collected according to the user's usage requirements, so as to generate corresponding data elements according to the user's usage requirements, and ultimately meet the user's different usage requirements. Of course, all the data to be governed obtained by the embodiments of the present invention are authorized and legal data.

[0036] S102, converting the data to be managed into corresponding digital signals;

[0037] That is, the data to be managed is converted into a corresponding digital signal according to the data information in the data to be managed. Specifically, the embodiment of the present invention converts each data information in the data to be managed into a corresponding value field according to a preset conversion principle to obtain digital signals corresponding to different data to be managed.

[0038] Among them, the preset conversion principle in the embodiment of the present invention is the correspondence between data information and value fields. Specifically, a corresponding mapping table can be set to store this correspondence. Of course, this correspondence can also be stored in other forms. Finally, it is set to facilitate corresponding searches during the conversion process.

[0039] In specific implementation, the embodiment of the present invention presets the value fields corresponding to each type of data information in the data to be managed, and converts the data to be managed into the corresponding value fields according to the correspondence between the data and the value fields. Specifically, the value can be a category code, etc.

[0040] For example, the student information can be set to 1001, the academic major to 1002, and so on. A value field is set for each piece of data information, and corresponding value fields are also set for each branch of data information under each piece of data information, so as to realize the conversion of the data to be managed into the corresponding digital signal.

[0041] S103, clustering and sorting the digital signals according to the usage change frequency and change range of each data information in the data to be managed, and the similarity and correlation relationship between the data information, and converting the digital signals into digital spectrums, so as to represent the change frequency and change range of each data in the data to be managed, and the similarity and correlation relationship between the data information through the digital spectrum;

[0042] That is to say, the embodiment of the present invention better characterizes the governance data by simultaneously introducing the usage change frequency, change amplitude, similarity and correlation relationship of each data information in the digital spectrum, so that the data element can better characterize the governance data.

[0043] Specifically, an embodiment of the present invention sets the data whose change frequency of the data information in the data to be governed is lower than a preset change frequency threshold as data of a core field with basic characteristics; and sets the data whose similarity between the name field of the data information in the data to be governed and its corresponding content is greater than a preset similarity threshold as data of a quality field with similarity characteristics; and then sets the data whose correlation between the data information in the data to be governed is greater than a preset correlation threshold as data of an energy field with correlation characteristics, thereby clustering and sorting the data from the dimensions of change frequency, change amplitude (i.e., the degree of change), and the similarity and correlation relationship between the data information, and converting them into corresponding digital spectra.

[0044] That is to say, the present invention clusters and sorts the digital signals from the core field, quality field and energy field dimensions respectively, and then converts the digital signals into corresponding digital spectrums.

[0045] It should be noted that the amplitude of change in data information can be calculated by calculating the ratio of the change value of the data information in the data to be governed to the original value. Of course, it can also be the ratio of the change value of the data information in the data to be governed to the value of the changed data information, and so on. It can be set according to needs.

[0046] In specific implementation, the horizontal axis of the digital spectrum can be set to represent the data of the core field, quality field and energy field, and the vertical axis can be used to represent the frequency of data changes. In addition, in specific implementation, the width occupied by each data on the horizontal axis can also be used to represent the amplitude of data changes, so that the digital spectrum can characterize data information from multiple dimensions such as change frequency, change amplitude, correlation and similarity.

[0047] It should be noted that the above is only an example of the digital spectrum of the present invention. During specific implementation, those skilled in the art may arbitrarily set the form of expression of the digital spectrum according to actual conditions. During specific implementation, those skilled in the art may also extract other characteristics of the data as needed to characterize the data information from other angles. The present invention does not specifically limit this.

[0048] In simple terms, the embodiment of the present invention clusters and sorts digital signals according to the amplitude of change and the dimensions of core fields, quality fields and energy fields. The amplitude of change of data information in the data to be governed can be measured according to the degree of change of the data information. For example, the amplitude of change of student payment data information can be considered from the perspective of meal card consumption and tuition fees, and so on.

[0049] Regarding the relevance and similarity of the data information in the data to be governed, for example, the professional title is related to the academic degree, the teaching experience is semantically similar to the age, and the academic degree information is semantically similar to the college diploma information, etc. In the specific implementation, the relevance and similarity are mainly to group similar and related fields together in the digital spectrum preparation stage.

[0050] In general, the embodiments of the present invention cluster and sort the data information in the governance data through various dimensions such as change frequency, change amplitude, correlation and similarity, so that the final digital spectrum can characterize the data information as accurately as possible, and then the generated data elements can accurately and effectively characterize the data, and finally effectively guarantee the accuracy of all subsequent processing and analysis of the data elements.

[0051] It should be noted that the specific values ​​of the preset change frequency threshold, the preset similarity threshold and the preset correlation threshold described in the embodiments of the present invention can be set by those skilled in the art based on experimental data, empirical data and actual needs. However, it should be emphasized that the values ​​of the preset change frequency threshold, the preset similarity threshold and the preset correlation threshold will directly affect the accuracy of the digital spectrum, so the settings of the above-mentioned thresholds should ensure their accuracy as much as possible to ensure the accuracy of the data elements finally generated.

[0052] For example, the core field is relatively stable, and different people have different values. For example, student information can be different school information, and the value field number is 1001, and its value is a certain university. The energy field changes frequently, such as student payment data information corresponding to 9003, and the value will change. After the digital signal is converted into a digital spectrum, the digital spectrum can accurately record the value content and changes of each value field. It should be noted that the digital spectrum in the embodiment of the present invention records the changes of data in the form of each value field.

[0053] In specific implementation, in an embodiment of the present invention, the data with a change frequency lower than a preset change frequency threshold is set to be data of a core field with basic characteristics, including: obtaining the change frequency of each type of data information in the data to be governed within a preset time period, and setting the data information with a change frequency lower than the preset change frequency threshold to be data of a core field with basic characteristics.

[0054] Specifically, in the embodiments of the present invention, both the change frequency and the change range can be measured according to the change of data information within a preset time period.

[0055] In addition, in the specific implementation, the analysis of correlation is to classify the value fields with the same characteristics into the same group. Specifically, the kmeans method can be used to divide the data information of the data to be governed into multiple categories and mark them separately. For example, k=3 is selected, and k data information is randomly selected from the data information of the data to be governed as the initial centroid (i.e., clustering center). The distance from each field to the centroid is calculated, and it is assigned to the class of the nearest centroid. The centroids of the obtained classes are recalculated multiple times until the new centroid is equal to the original centroid or less than the specified threshold, and the algorithm ends. The similarity between data information can be calculated based on the distance from the value field to the centroid. The smaller the distance, the higher the similarity.

[0056] From the above, it can be seen that the digital spectrum generated in the embodiment of the present invention can characterize the change frequency and change range of the value field of the data information in the data to be governed, as well as the similarity of the content of the data information and the correlation between the characteristic variables of the value field of the data information. In short, the digital spectrum in the embodiment of the present invention can characterize the change frequency, change range, similarity and correlation of the data, which enables the data elements generated based on the digital spectrum of the present invention to also characterize the change frequency, change range similarity and correlation of the data. Therefore, the data elements can replace the original data for data circulation, thereby ensuring the effective use of data while ensuring data security.

[0057] S104: extracting data element features from the digital spectrum through a preset data element model, and generating data elements based on the data element features, so as to replace original data through the data elements for data trading, circulation and use.

[0058] Among them, in the embodiment of the present invention, the same part and the different part of the digital spectrum of each data to be managed are extracted to form the data element characteristics, that is, the data element characteristics in the embodiment of the present invention include the same characteristic attributes and the different characteristic attributes in the digital spectrum of different data to be managed, that is, the data element characteristics in the embodiment of the present invention are data meta-information, and the data element model in the embodiment of the present invention is a preset dynamic programming objective function. Specifically, the embodiment of the present invention extracts data element characteristics from the digital spectrum of different data to be managed through the dynamic programming objective function, and generates data elements based on the data element characteristics, wherein the data element characteristics include the same characteristic attributes and the different characteristic attributes between the digital spectrums of different data to be managed.

[0059] In specific implementation, the width of the digital spectrum can be set to correspond to the change amplitude attribute of the content of each value field, and the height can correspond to the change frequency of each value field. And the data element characteristics of different data to be governed can be simplified by the commonalities and differences between the two to reduce the complexity of the data element. Among them, the core field is relatively stable, the values ​​of different data to be governed are different, and the values ​​of the same type of data to be governed are generally the same. For example, the student information field ZD1001 represents a certain university, and the student payment field ZD9003 includes meal fees, professional tuition fees, etc., so students A and B of different majors may have different widths in the student payment field. These can all be reflected through the characteristics of data elements, and the generated data elements can be set to characterize the data characteristics of different data to be governed. Finally, data elements are used to replace data for circulation and interaction, thereby realizing data circulation under the premise of effectively ensuring data security.

[0060] Specifically, the data element model in the embodiment of the present invention is implemented by a dynamic programming algorithm, which is: , set the data element characteristics to X1, X2, ..., X k , under each data component feature, the attributes of the digital spectrum of different data to be managed (the attribute is the field name under each data information in the data to be managed, such as faculty name, age, gender, teaching experience, subject, etc.) and the value are different. Suppose the value of the jth attribute of the data component feature X1 of the i-th data to be managed is X 1ij , i, j and k are all natural numbers, n is the number of data element features, is the numerical difference between the data element characteristics, which is obtained by taking the data element characteristic of the i-th data to be managed as a benchmark and comparing the data element characteristics of other data to be managed with the benchmark data element characteristics.

[0061] In specific implementation, the embodiment of the present invention is The data value of the data to be governed is calculated, and based on the calculated data value of the data element, the value of the data element in the data market is further measured to achieve data pricing, thereby facilitating the circulation and use of the data element in the data market. Finally, the present invention outputs the generated data element for further processing and analysis of the data, thereby facilitating the listing and trading of the data element, thereby creating the maximum use value of the data.

[0062] The method described in the embodiment of the present invention will be explained and illustrated in detail below through a specific example:

[0063] An embodiment of the present invention provides a method for generating a data element based on a digital spectrum, which specifically includes the following steps:

[0064] (1) Data collection of data components: that is, collecting authorized data to be managed, and converting it into digital signals by analyzing and summarizing the collected data to be managed;

[0065] (2) Spectrum processing of data elements: Cluster and sort the data elements according to the frequency of use change, degree of change, similarity and correlation of the data information in the data to be managed. The core fields are those with low frequency of use change and basic characteristics, that is, the frequency of change of each value field within a certain time range is counted. The quality fields are those with general frequency of use change and similarity characteristics, and the energy fields are those with high frequency of use change and correlation characteristics. These digital signals are interval transformed or encoded to convert them into digital spectra.

[0066] That is to say, the embodiment of the present invention judges based on the frequency of change. The basically unchanged and very stable features are called basic features, the names of data information and the contents of data information are similar, which are called similarity features, and the strong correlation between data information variables is called correlation features.

[0067] Specifically, the digital spectrum in the embodiment of the present invention represents the frequency and amplitude of changes of each data information, as well as the similarity and correlation between the data information through the width, height and sorting position of each value field in the digital signal, thereby achieving effective use of data while effectively ensuring the security of personal data.

[0068] (3) Data component extraction: A dynamic programming algorithm is used to extract data component features from the digital spectrum. These data component features can represent the frequency content and variation amplitude of the signal. , where f(n,W) represents the maximum value that can be obtained when the amount of information is W in the first n fields, wn and vn represent the value and amount of information of the nth feature respectively, and f maximizes the amount of information contained in the data element. The digital spectrum is mainly a data element representation method generated to hide the original data.

[0069] (4) Output of data elements: The extracted data element features are output to a computer, controller or other device for further processing and analysis.

[0070] Accordingly, an embodiment of the present invention further provides a device for generating data elements based on a digital spectrum, see Figure 2 , the device comprises:

[0071] An acquisition unit, used to acquire the data to be governed, and convert the data to be governed into corresponding digital signals according to data information in the data to be governed, wherein the data to be governed is data that can be traded, circulated and used after being allowed to be governed accordingly;

[0072] a first processing unit, configured to cluster and sort the digital signals according to the usage change frequency and change range of each data information in the data to be managed, and the similarity and correlation relationship between the data information, and convert the digital signals into digital spectrums, so as to represent the change frequency and change range of each data information in the data to be managed, and the similarity and correlation relationship between the data information through the digital spectrum;

[0073] The second processing unit is used to extract data element features from the digital spectrum through a preset data element model, and generate data elements based on the data element features, so as to replace the original data through the data elements for data trading, circulation and use.

[0074] The embodiment of the present invention converts the data to be governed into corresponding digital signals through the device for generating data elements based on digital spectrum, and further converts it into digital spectrum. Then, the digital spectrum is set to characterize the change frequency and change amplitude of each data information in the data to be governed, as well as the similarity and correlation between the data information. Then, based on the digital spectrum, data element characteristics are extracted and data elements are generated, so that the data elements can be used to replace the original data, so that the characteristics of the data can be characterized by the data elements during the circulation of data elements, thereby effectively reducing the risk of data privacy leakage, thereby improving data utilization, and ultimately greatly improving user experience.

[0075] Furthermore, the acquisition unit of the embodiment of the present invention generates a request for a data element based on the received user, and acquires the corresponding data to be governed based on the request, wherein the request in the embodiment of the present invention includes information on the data to be governed required for generating the data element, that is, including each data under the data to be governed required for the generated data element and the scope of the data to be governed, etc.

[0076] In specific implementation, in an embodiment of the present invention, the acquisition unit is further used to convert each data information in the data to be managed into a corresponding value field according to a preset conversion principle to obtain digital signals of different data to be managed.

[0077] Among them, the preset conversion principle in the embodiment of the present invention is the correspondence between data and value fields, that is, the embodiment of the present invention can set a corresponding mapping table to store this correspondence. Of course, this correspondence can also be stored in other forms. Finally, it is set to facilitate corresponding searches during the conversion process.

[0078] In addition, in the specific implementation, the first processing unit in the embodiment of the present invention simultaneously introduces the usage change frequency, change amplitude, similarity and correlation relationship of each data information in the data into the digital spectrum to better characterize the data, thereby facilitating the data element to better characterize the data.

[0079] Specifically, the first processing unit of the embodiment of the present invention is to set the data whose change frequency of the data information in the data to be governed is lower than the preset change frequency threshold as the data of the core field with basic characteristics; and set the data whose similarity between the name field of the data information in the data to be governed and its corresponding content is greater than the preset similarity threshold as the data of the quality field with similarity characteristics; and then set the data whose correlation between the data information in the data to be governed is greater than the preset correlation threshold as the data of the energy field with correlation characteristics, so as to cluster and sort the data from the dimensions of change frequency, change amplitude (i.e., the degree of change), and the similarity and correlation relationship between the data information, and convert them into corresponding digital spectra.

[0080] That is to say, the present invention clusters and sorts the digital signals from the core field, quality field and energy field dimensions respectively, and then converts the digital signals into corresponding digital spectrums.

[0081] Furthermore, in the embodiment of the present invention, the second processing unit is further configured to extract data component features from the digital spectrum by using a preset dynamic programming algorithm, generate data components based on the data component features, and generate data components by using the formula to calculate the data value of the data, so as to further measure the value of the data element in the data market based on the calculated data value of the data element, thereby realizing the pricing of the data;

[0082] The data element characteristics in the embodiment of the present invention include the same characteristic attributes and different characteristic attributes between the digital spectra of different data to be managed;

[0083] The preset dynamic programming algorithm is: ; Set the data element characteristics to X1, X2, ..., X k , under each data component feature, the attributes and values ​​of the digital spectrum of different data to be managed are different. Suppose the value of the jth attribute of the data component feature X1 of the i-th data to be managed is X 1ij , where i, j and k are all natural numbers, and n is the number of data element features. is the numerical difference between the data element characteristics, which is obtained by taking the data element characteristic of the i-th data to be managed as a benchmark and comparing the data element characteristics of other data to be managed with the benchmark data element characteristics.

[0084] The relevant contents of the embodiments of the device of the present invention can be understood by referring to the embodiments of the method of the present invention, and will not be discussed in detail here.

[0085] In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the method for generating a data element based on a digital spectrum described in any one of the method embodiments of the present invention is implemented. For details, please refer to the method embodiments of the present invention for understanding, and no detailed discussion is given here.

[0086] In general, the present invention converts all the data to be governed into corresponding digital signals, and further converts them into digital spectra. The digital spectrum is set so that it can characterize the change frequency and change amplitude of each data information in the data to be governed, as well as the similarity and change frequency of the correlation between the data information. Then, based on the digital spectrum, data element characteristics are extracted and data elements are generated. The data elements are used to replace the original data (i.e., the above-mentioned data to be governed). In this way, the characteristics of the data can be characterized by the data elements during the circulation of data elements, thereby effectively reducing the risk of data privacy leakage, thereby improving data utilization, and ultimately greatly improving user experience.

[0087] Although the preferred embodiments of the present invention have been disclosed for illustrative purposes, those skilled in the art will appreciate that various modifications, additions and substitutions are possible, and thus, the scope of the present invention should not be limited to the above embodiments.

Claims

1. A method for generating data elements based on a digital spectrum, characterized in that: include: Acquire the data to be governed, and convert the data to be governed into corresponding digital signals according to data information in the data to be governed, wherein the data to be governed is data that can be traded and used after being allowed to be governed accordingly; Clustering and sorting the digital signals according to the usage change frequency and change range of each data information in the data to be managed, as well as the similarity and correlation relationship between the data information, and converting the digital signals into digital spectrums, so as to represent the change frequency and change range of each data information in the data to be managed, as well as the similarity and correlation relationship between the data information through the digital spectrum; Extracting data element features from the digital spectrum through a preset data element model, and generating data elements based on the data element features, so as to replace original data for data trading and use through the data elements; Converting the data to be managed into a corresponding digital signal according to the data information in the data to be managed, including: converting all the data information in the data to be managed into a corresponding value field according to a preset conversion principle to obtain a digital signal corresponding to the data to be managed; The digital spectrum represents the change frequency and change amplitude of each data in the data to be managed, as well as the similarity and correlation between each data through the width, height and sorting position of each value field in the digital signal; The extracting data element features from the digital spectrum by using a preset data element model and generating data elements based on the data element features includes: Extracting data element features from the digital spectrum by a preset dynamic programming algorithm, and generating data elements based on the data element features, wherein the data element features include common feature attributes and different feature attributes between digital spectrums of different data to be governed; The preset dynamic programming algorithm is: ; Set the data element characteristics to X1, X2, ..., X k , under each data component feature, the attributes and values ​​of the digital spectrum of different data to be managed are different. Suppose the value of the jth attribute of the data component feature X1 of the i-th data to be managed is X 1ij , where i, j and k are all natural numbers, n is the number of data element features, is the numerical difference between the data element characteristics, which is obtained by taking the data element characteristic of the i-th data to be managed as a benchmark and comparing the data element characteristics of other data to be managed with the benchmark data element characteristics.

2. The method according to claim 1, characterized in that The obtaining of the data to be governed includes: A request from a user to generate a data element is received, and corresponding data to be managed is acquired according to the request, wherein the request includes information of the data to be managed required to generate the data element.

3. The method according to claim 1, characterized in that Clustering and sorting the digital signals according to the usage change frequency and change range of each data information in the data to be managed, and the similarity and correlation between the data information, and converting the digital signals into digital spectrum, including: The data whose change frequency of data information in the data to be managed is set to be data of core fields with basic characteristics, which is lower than a preset change frequency threshold; The data whose similarity between the name field of the data information to be managed and the content corresponding thereto is greater than a preset similarity threshold is set as data of the quality field having similarity characteristics; The data whose correlation between data information in the data to be managed is set to be data of an energy field with correlation characteristics, if the correlation between data information is greater than a preset correlation threshold; The data signals are clustered and sorted based on the dimensions of change frequency, change amplitude, and the similarity and correlation between the data information, and converted into corresponding digital spectra.

4. The method according to claim 3, characterized in that The step of setting the data whose change frequency of data information in the data to be managed is lower than a preset change frequency threshold as data of core fields with basic characteristics includes: The change frequency of each data information in the data to be managed within a preset time period is obtained, and the data information with a change frequency lower than the preset change frequency threshold is set as the data of the core field with basic characteristics.

5. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: pass Calculate the data value of the data element, where f(n,W) represents the maximum value obtained when the information amount of the data to be managed is W among the first n data element features, and wn and vn represent the value and information amount of the nth data element feature, respectively; The value of the data element circulated in the data market is measured based on the calculated data value of the data element, so as to realize the circulation and use of the data element in the data market.

6. A device for generating data elements based on a digital spectrum, characterized in that: The device comprises: An acquisition unit is used to acquire the data to be governed, and convert the data to be governed into corresponding digital signals according to the data information in the data to be governed, that is, convert all the data information in the data to be governed into corresponding value fields according to a preset conversion principle to obtain a digital signal corresponding to the data to be governed, wherein the data to be governed is data that can be traded, circulated and used after being allowed to be governed accordingly; a first processing unit, configured to cluster and sort the digital signals according to the usage change frequency and change range of each data information in the data to be managed, and the similarity and correlation relationship between the data information, and convert the digital signals into digital spectrums, so as to represent the change frequency and change range of each data information in the data to be managed, and the similarity and correlation relationship between the data information through the digital spectrum, wherein the digital spectrum represents the change frequency and change range of each data in the data to be managed, and the similarity and correlation relationship between the data through the width and height occupied by each value field in the digital signal and the sorting position; The second processing unit is used to extract data element features from the digital spectrum through a preset data element model, and generate data elements based on the data element features, so as to replace the original data for data trading and use through the data elements, that is, to extract data element features from the digital spectrum through a preset dynamic programming algorithm, and generate data elements based on the data element features, wherein the data element features include the same feature attributes and different feature attributes between the digital spectra of different data to be governed; the preset dynamic programming algorithm is ; Set the data element characteristics to X1, X2, ..., X k , under each data component feature, the attributes and values ​​of the digital spectrum of different data to be managed are different. Suppose the value of the jth attribute of the data component feature X1 of the i-th data to be managed is X 1ij , where i, j and k are all natural numbers, n is the number of data element features, is the numerical difference between the data element characteristics, which is obtained by taking the data element characteristic of the i-th data to be managed as a benchmark and comparing the data element characteristics of other data to be managed with the benchmark data element characteristics.

7. A computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method for generating a data element based on a digital spectrum as claimed in any one of claims 1 to 5.

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