Data resource sharing method and data resource sharing platform

Abstract

The invention discloses a data resource sharing method and a data resource sharing platform. The data resource sharing method comprises the following steps: receiving data resource sharing request information sent by a data requester; analyzing the request information to obtain a target analysis result; obtaining a shared data resource based on the target analysis result, and evaluating the shared data resource; when it is determined that the evaluation result is qualified, data transmission channel information for transmitting the shared data resource to the data requester is obtained; transmitting the shared data resource based on the data transmission channel to complete data resource sharing; the request information is analyzed, so that the requirement can be accurately understood, and the shared data resource which better meets the requirement can be obtained; the quality and reliability of the data are ensured by evaluating the shared data, and valuable data are provided for a data requester; and the qualified transmission channel is determined, so that the safety and the stability of the data in the transmission process are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of data sharing, and in particular to a data resource sharing method and a data resource sharing platform. Background Art

[0002] With the development of Internet communications, big data technology has become more mature. As one of the branches of big data technology, data resource sharing has gradually been applied to cloud business processing. Data resource sharing means that users in different places using different computers and different software can read other people's data and perform various operations, calculations and analyses. However, faced with the huge and rapidly growing amount of data, business personnel are generally confused about how to quickly obtain the required shared data resources in the actual use and analysis of data resources. Based on the data request information sent by the data requester, after analyzing the data sharing request, the data sharing party (1) searches the entire database, table and data items of the requested shared data resources. The search scope is large, time-consuming and not targeted; (2) the quality of the shared data resources retrieved is not controlled, resulting in the search results often not being the data resources that the data requester really needs; (3) during the transmission of shared data resources, the transmission efficiency is very low due to the transmission channel.

[0003] Therefore, there is an urgent need for a data resource sharing method and a data resource sharing platform to solve the above problems. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems in the above-mentioned technologies to a certain extent. To this end, the first aspect of the present invention aims to propose a data resource sharing method, wherein the analysis of request information helps to accurately understand the requirements, thereby obtaining shared data resources that better meet the requirements; the evaluation of shared data ensures the quality and reliability of the data, and provides valuable data for the data requester; and the determination of qualified transmission channels ensures the security and stability of the data during the transmission process.

[0005] A second aspect of the present invention aims to provide a data resource sharing platform.

[0006] To achieve the above object, a first aspect of the present invention provides a data resource sharing method, comprising:

[0007] Receiving data resource sharing request information sent by a data requester;

[0008] Analyze the request information to obtain a target analysis result;

[0009] Acquire shared data resources based on the target analysis results, and evaluate the shared data resources;

[0010] When it is determined that the evaluation result is qualified, obtaining data transmission channel information for transmitting the shared data resource to the data requesting party;

[0011] The shared data resource is transmitted based on the data transmission channel to complete data resource sharing.

[0012] Preferably, analyzing the request information to obtain a target analysis result includes:

[0013] Analyze the request information to determine the requester identity authentication information, data category information, data range information and data authority verification information; wherein the data category information corresponds to the data range information one-to-one, and the data range information corresponds to the data authority verification information one-to-one;

[0014] Comparing the requester identity authentication information with a preset data resource sharing identity authentication table to determine a first analysis result;

[0015] Compare the data category information with the preset data sharing category table to determine the target data category information;

[0016] Calculate the similarity between the data range information corresponding to the data category information and the target data range information corresponding to the target data category information;

[0017] When it is determined that the similarity is greater than or equal to the preset similarity threshold, obtaining target data authority verification information corresponding to the target data range information;

[0018] Comparing the data permission verification information with the target data permission verification information to determine a second analysis result;

[0019] Based on the first analysis result and the second analysis result, a target analysis result is determined.

[0020] Preferably, evaluating the shared data resource includes:

[0021] Evaluate each category of data in the shared data resource based on a preset data evaluation algorithm to obtain an evaluation value corresponding to each category of data;

[0022] Traverse all category data and obtain several evaluation values;

[0023] The average of the sum of several evaluation values ​​is taken as the evaluation value of the shared data resource.

[0024] Preferably,

[0025]

[0026] Among them, P irepresents the evaluation value of the i-th category data; n represents the total number of data categories in the shared data resource; ρ i Indicates the amount of data in the i-th category; q i Represents the weight value of the i-th category data; T i，k represents the feature of the kth data in the i-th category data; F j Indicates the characteristic parameter of the jth byte in the shared data resource; m i Indicates the total number of bytes in the i-th category data of the shared data resource; Represents the mean of the type coefficient differences of shared data resources; r i Represents the type coefficient of the i-th category data; D i represents the data range of the i-th category data; d represents the mean of the data range in the request information; G represents the total range of the data in the request information.

[0027] Preferably, before evaluating the shared data resource, the method further comprises:

[0028] Clustering the shared data resources to obtain a plurality of shared sub-data groups;

[0029] Take any shared sub-data group as the target data group;

[0030] Obtaining a timestamp in a target data group; sorting the target data group based on the timestamp to obtain sequence data corresponding to the target data group;

[0031] Segmenting the sequence data based on a preset step length to obtain a plurality of sequence sub-data;

[0032] Performing anomaly detection on the plurality of sequence sub-data to obtain a plurality of initial abnormal sequence sub-data;

[0033] Randomly select two initial abnormal sequence sub-data to obtain first abnormal sequence sub-data and second abnormal sequence sub-data;

[0034] Calculate the correlation coefficient between each value in the first abnormal sequence sub-data and the value at the corresponding position in the second abnormal sequence sub-data;

[0035] Deleting the corresponding value when the correlation coefficient is greater than or equal to the preset correlation threshold value, to obtain the first abnormal sequence sub-data after the value is deleted and the second abnormal sequence sub-data after the value is deleted;

[0036] Traverse all the initial abnormal sequence sub-data to obtain several initial abnormal sequence sub-data after deleting values;

[0037] The second similarities between the initial abnormal sequence sub-data after deleting a plurality of values ​​are calculated, and when it is determined that the maximum value of the second similarities is less than a preset similarity threshold, deduplication of the shared data resource is completed.

[0038] Preferably, performing anomaly detection on the plurality of sequence sub-data to obtain a plurality of initial abnormal sequence sub-data includes:

[0039] Randomly select a sequence sub-data as the target sequence sub-data;

[0040] respectively calculating first similarities between the target sequence sub-data and sequence sub-data other than the target sequence sub-data;

[0041] Comparing the first similarity with a preset similarity threshold;

[0042] When the first similarity is greater than or equal to a preset similarity threshold, the corresponding sequence sub-data is marked as abnormal;

[0043] Traversing each sequence sub-data, and marking the corresponding sequence sub-data as abnormal when the first similarity is greater than or equal to a preset similarity threshold;

[0044] Count the number of abnormal marks corresponding to each sequence sub-data;

[0045] The sequence sub-data corresponding to the abnormal marking times being greater than or equal to the preset marking threshold is used as the initial abnormal sequence sub-data.

[0046] Preferably, transmitting the shared data resource based on the data transmission channel includes:

[0047] Dividing each category of data in the shared data resource into a plurality of data groups; compressing the plurality of data groups to obtain a plurality of compressed data packets;

[0048] Extracting a preset ratio of the plurality of compressed data packets to obtain a plurality of test compressed data packets;

[0049] Transmitting the plurality of test compressed data packets respectively based on the data transmission channels, and determining a first evaluation value of each data transmission channel;

[0050] Comparing the first evaluation value with a preset transmission evaluation threshold; taking the data transmission channel corresponding to when the first evaluation value is greater than or equal to the preset transmission evaluation threshold as the initial data transmission channel, to obtain a plurality of initial data transmission channels;

[0051] Acquire historical transmission information within a preset time period corresponding to the plurality of initial data transmission channels;

[0052] Determine a historical evaluation value corresponding to the initial data transmission channel based on the historical transmission information to obtain a second evaluation value;

[0053] Calculate the difference between the first evaluation value corresponding to each initial data transmission channel and the second evaluation value corresponding to each initial data transmission channel to obtain an evaluation deviation value;

[0054] Comparing the evaluation deviation value with a preset deviation value threshold;

[0055] The initial data transmission channel corresponding to when the evaluation deviation value is less than or equal to the preset deviation value threshold is used as the target data transmission channel;

[0056] The plurality of compressed data packets are transmitted based on the target data transmission channel.

[0057] Preferably, the plurality of data groups are compressed to obtain a plurality of compressed data packets, including:

[0058] Take any data group as the target data group;

[0059] Binarizing the target data group to obtain a data length corresponding to the target data group;

[0060] Allocate and encode the data length of the target data group based on a preset ratio, and determine the encoding sequence number corresponding to the target data group;

[0061] Determine a coding table based on the data length of the target data group and the coding sequence number corresponding to the target data group;

[0062] Encode the target data group based on the encoding table to obtain encoding information corresponding to the target data group;

[0063] Based on the coding information, determining a coding matrix corresponding to the target data group;

[0064] Determining a data identifier of the target data group based on the encoding matrix;

[0065] Based on the data identifier, the target data group and the previous data group are aggregated and compressed to obtain a compressed data packet; each data group is traversed to obtain a plurality of compressed data packets.

[0066] Preferably, determining the first evaluation value of each data transmission channel includes:

[0067]

[0068] Wherein, Q represents the first evaluation value of the data transmission channel; ln() represents the logarithmic function with the natural constant e as the base; n represents the total number of the tested compressed data packets; Tci represents the transmission delay when transmitting the i-th test compressed data packet; T bi represents the transmission delay of the i-th test compressed data packet; T0 represents the preset standard delay; τ i Indicates the length of the i-th test compressed data packet; t i represents the time consumed to transmit the i-th test compressed data packet; v represents the transmission rate of the data transmission channel; f represents the sending frequency of the test compressed data packet; f0 represents the sending frequency of the preset data packet; It represents the average bandwidth of transmitting several test compressed data packets; G0 represents the bandwidth of the data transmission channel.

[0069] To achieve the above-mentioned purpose, a second aspect of the present invention discloses a data resource sharing platform, including:

[0070] A receiving module, used for receiving data resource sharing request information sent by a data requester;

[0071] An analysis module, used to analyze the request information to obtain a target analysis result;

[0072] An evaluation module, used to obtain shared data resources based on the target analysis results and evaluate the shared data resources;

[0073] An acquisition module, used to acquire data transmission channel information for transmitting the shared data resource to the data requester when it is determined that the evaluation result is qualified;

[0074] The sharing module is used to transmit the shared data resources based on the data transmission channel to complete data resource sharing.

[0075] The present invention discloses a data resource sharing method and a data resource sharing platform. Through a clear process, the data resource sharing request of the user can be quickly responded to, and the time consumption of the intermediate links can be reduced; the analysis of the request information is helpful to accurately understand the demand, so as to obtain the shared data resources that better meet the requirements; the evaluation of the shared data ensures the quality and reliability of the data, and provides valuable data for the data requester; the qualified transmission channel is determined to ensure the security and stability of the data during the transmission process; the data resources can be better integrated and utilized, the waste of resources can be avoided, and the overall resource utilization efficiency can be improved.

[0076] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0077] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0079] Figure 1 is a flow chart of a data resource sharing method according to an embodiment of the present invention;

[0080] Figure 2 is a flow chart of obtaining a target analysis result according to an embodiment of the present invention;

[0081] Figure 3 It is a block diagram of a data resource sharing platform according to an embodiment of the present invention. DETAILED DESCRIPTION

[0082] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0083] Example 1

[0084] like Figure 1 As shown, a data resource sharing method includes steps S1-S5:

[0085] S1: receiving data resource sharing request information sent by the data requester;

[0086] S2: Analyze the request information to obtain a target analysis result;

[0087] S3: Acquire shared data resources based on the target analysis results, and evaluate the shared data resources;

[0088] S4: When it is determined that the evaluation result is qualified, obtaining data transmission channel information for transmitting the shared data resource to the data requesting party;

[0089] S5: Transmitting the shared data resource based on the data transmission channel to complete data resource sharing.

[0090] In this embodiment, the target analysis result includes the verification result of the identity of the data requester and the verification result of the data category information, data range information, and data authority verification information. When the verification is passed, the shared data resources corresponding to the request information are obtained.

[0091] The beneficial effects of the above technical solution are: through a clear process, it can quickly respond to users' data resource sharing requests and reduce the time consumption of intermediate links; the analysis of request information helps to accurately understand the needs, so as to obtain shared data resources that better meet the requirements; the evaluation of shared data ensures the quality and reliability of the data and provides valuable data for the data requester; determines the qualified transmission channel to ensure the security and stability of the data during the transmission process; and can better integrate and utilize data resources, avoid resource waste, and improve the overall resource utilization efficiency.

[0092] Example 2

[0093] like Figure 2 As shown, the request information is analyzed to obtain target analysis results, including:

[0094] Analyze the request information to determine the requester identity authentication information, data category information, data range information and data authority verification information; wherein the data category information corresponds to the data range information one-to-one, and the data range information corresponds to the data authority verification information one-to-one;

[0095] Comparing the requester identity authentication information with a preset data resource sharing identity authentication table to determine a first analysis result;

[0096] Compare the data category information with the preset data sharing category table to determine the target data category information; perform similarity calculation on the data range information corresponding to the data category information and the target data range information corresponding to the target data category information; when it is determined that the similarity is greater than or equal to the preset similarity threshold, obtain the target data authority verification information corresponding to the target data range information; compare the data authority verification information with the target data authority verification information to determine the second analysis result;

[0097] Based on the first analysis result and the second analysis result, a target analysis result is determined.

[0098] In this embodiment, the data category information is the data category of the data requested to be shared by the requesting party.

[0099] In this embodiment, the data range information is the data range corresponding to each data category in the shared data requested by the requesting party.

[0100] In this embodiment, the data authority verification information is whether the requesting party has the authority to share the data range corresponding to each data category in the shared data requested by the requesting party.

[0101] In this embodiment, the similarity calculation method includes but is not limited to Euclidean distance similarity calculation.

[0102] The beneficial effects of the above technical solution are: through multi-faceted analysis of request information, including identity authentication, data category, scope and authority, the security and accuracy of data acquisition are ensured, and only requests with legal identities and in compliance with authority can be effectively processed, thereby ensuring the security of data resources; by utilizing the correspondence between categories and scopes and similarity calculations, appropriate data can be accurately matched, thereby improving the accuracy of data retrieval and provision; through step-by-step analysis and comparison, the reliability and rigor of the entire process are enhanced, thereby avoiding the provision of erroneous data.

[0103] Example 3

[0104] The shared data resource is evaluated, including:

[0105] Evaluate each category of data in the shared data resource based on a preset data evaluation algorithm to obtain an evaluation value corresponding to each category of data;

[0106] Traverse all category data and obtain several evaluation values;

[0107] The average of the sum of several evaluation values ​​is taken as the evaluation value of the shared data resource.

[0108] In this embodiment, the category data in the shared data resources include user basic information category: such as name, age, gender, contact information, etc.; transaction data category: such as purchase records, sales data, order information, etc.; behavior data category: such as browsing records, operation records, access trajectories, etc.; business data category: such as product information, service content, project data, etc.; statistical data category: such as various summary data, analysis indicator data, etc.; geographic data category: such as location information, regional division, etc.; device data category: such as device model, usage status, etc.

[0109] The beneficial effects of the above technical solution are: each category of data is evaluated to ensure a comprehensive consideration of shared data resources and avoid one-sided evaluation; evaluation is performed based on a preset data evaluation algorithm to reduce the influence of subjective factors and make the evaluation results more objective and credible; by calculating the evaluation value of each category of data and taking the average as the overall evaluation value, the comprehensive quality of shared data resources can be more accurately reflected; specific evaluation values ​​are obtained to facilitate comparison and analysis of shared data resources from different batches or sources; special evaluation algorithms can be designed according to the characteristics of different categories of data, so as to better highlight the important features and quality indicators of each type of data.

[0110] Example 4

[0111] The preset data evaluation algorithm includes:

[0112]

[0113] Among them, P i represents the evaluation value of the i-th category data; n represents the total number of data categories in the shared data resource; ρ i Indicates the amount of data in the i-th category; q i Represents the weight value of the i-th category data; T i，k represents the feature of the kth data in the i-th category data; F j Indicates the characteristic parameter of the jth byte in the shared data resource; m i Indicates the total number of bytes in the i-th category data of the shared data resource; Represents the mean of the type coefficient differences of shared data resources; r i Represents the type coefficient of the i-th category data; D i represents the data range of the i-th category data; d represents the mean of the data range in the request information; G represents the total range of the data in the request information.

[0114] The beneficial effects of the above technical solution are: through multiple factors such as data category, data volume, weight, characteristics, byte feature parameters, type coefficient, data range, etc., the data can be evaluated comprehensively and meticulously; through the setting of various characteristics and weights, the uniqueness and importance of different data are highlighted, making the evaluation more targeted; the overall characteristics of shared data resources and factors related to the requested information, such as data range, are taken into account, so that the evaluation can better adapt to different scenarios and needs; complex calculation formulas help to more accurately quantify the value and quality of data, reduce subjective bias, and improve the accuracy of evaluation results.

[0115] Example 5

[0116] Before evaluating the shared data resource, it also includes:

[0117] Clustering the shared data resources to obtain a plurality of shared sub-data groups;

[0118] Take any shared sub-data group as the target data group;

[0119] Obtaining a timestamp in a target data group; sorting the target data group based on the timestamp to obtain sequence data corresponding to the target data group;

[0120] Segmenting the sequence data based on a preset step length to obtain a plurality of sequence sub-data;

[0121] Performing anomaly detection on the plurality of sequence sub-data to obtain a plurality of initial abnormal sequence sub-data;

[0122] Randomly select two initial abnormal sequence sub-data to obtain first abnormal sequence sub-data and second abnormal sequence sub-data;

[0123] Calculate the correlation coefficient between each value in the first abnormal sequence sub-data and the value at the corresponding position in the second abnormal sequence sub-data;

[0124] Deleting the corresponding value when the correlation coefficient is greater than or equal to the preset correlation threshold value, to obtain the first abnormal sequence sub-data after the value is deleted and the second abnormal sequence sub-data after the value is deleted;

[0125] Traverse all the initial abnormal sequence sub-data to obtain several initial abnormal sequence sub-data after deleting values;

[0126] The second similarities between the initial abnormal sequence sub-data after deleting a plurality of values ​​are calculated, and when it is determined that the maximum value of the second similarities is less than a preset similarity threshold, deduplication of the shared data resource is completed.

[0127] In this embodiment, the clustering method includes but is not limited to K-Means clustering.

[0128] In this embodiment, the calculation method of the correlation coefficient includes but is not limited to the Pearson correlation coefficient algorithm.

[0129] The beneficial effects of the above technical solution are: through a series of operations such as clustering, anomaly detection and deduplication, the data is effectively cleaned and optimized, and the accuracy and reliability of shared data resources are improved; duplicate data is removed to ensure data consistency and reduce redundant information; the processed data is more orderly and refined, which is conducive to subsequent data analysis and processing work and improves overall efficiency; after cleaning abnormal data and duplicate data, the shared data resources are made more usable and valuable; the use of correlation coefficients and similarity thresholds ensures that the processed sequence data is more reasonable and meets actual needs.

[0130] Example 6

[0131] Anomaly detection is performed on the plurality of sequence sub-data to obtain a plurality of initial abnormal sequence sub-data, including:

[0132] Randomly select a sequence sub-data as the target sequence sub-data;

[0133] respectively calculating first similarities between the target sequence sub-data and sequence sub-data other than the target sequence sub-data;

[0134] Comparing the first similarity with a preset similarity threshold;

[0135] When the first similarity is greater than or equal to a preset similarity threshold, the corresponding sequence sub-data is marked as abnormal;

[0136] Traversing each sequence sub-data, and marking the corresponding sequence sub-data as abnormal when the first similarity is greater than or equal to a preset similarity threshold;

[0137] Count the number of abnormal marks corresponding to each sequence sub-data;

[0138] The sequence sub-data corresponding to the abnormal marking times being greater than or equal to the preset marking threshold is used as the initial abnormal sequence sub-data.

[0139] The beneficial effects of the above technical solution are: by calculating the similarity and comparing it with the threshold, the sequence sub-data that may have anomalies can be found more accurately; all sequence sub-data are traversed to ensure the comprehensiveness and completeness of anomaly detection; further screening is performed according to the number of anomaly markings to improve the reliability of determining the initial abnormal sequence sub-data; timely discovery and marking of abnormal data is conducive to subsequent targeted processing of the data and improves the reliability of the overall data.

[0140] Example 7

[0141] Transmitting the shared data resource based on the data transmission channel includes:

[0142] Dividing each category of data in the shared data resource into a plurality of data groups; compressing the plurality of data groups to obtain a plurality of compressed data packets;

[0143] Extracting a preset ratio of the plurality of compressed data packets to obtain a plurality of test compressed data packets;

[0144] Transmitting the plurality of test compressed data packets respectively based on the data transmission channels, and determining a first evaluation value of each data transmission channel;

[0145] Comparing the first evaluation value with a preset transmission evaluation threshold; taking the data transmission channel corresponding to when the first evaluation value is greater than or equal to the preset transmission evaluation threshold as the initial data transmission channel, to obtain a plurality of initial data transmission channels;

[0146] Acquire historical transmission information within a preset time period corresponding to the plurality of initial data transmission channels;

[0147] Determine a historical evaluation value corresponding to the initial data transmission channel based on the historical transmission information to obtain a second evaluation value;

[0148] Calculate the difference between the first evaluation value corresponding to each initial data transmission channel and the second evaluation value corresponding to each initial data transmission channel to obtain an evaluation deviation value;

[0149] Comparing the evaluation deviation value with a preset deviation value threshold;

[0150] The initial data transmission channel corresponding to when the evaluation deviation value is less than or equal to the preset deviation value threshold is used as the target data transmission channel;

[0151] The plurality of compressed data packets are transmitted based on the target data transmission channel.

[0152] The working principle of the above technical solution is: extract some compressed data packets as test compressed data packets according to a preset ratio. Then transmit these test data packets respectively through multiple data transmission channels (such as channel A, channel B, channel C), and determine the first evaluation value of each channel according to factors such as transmission speed and stability. Assuming that the first evaluation values ​​of channel A and channel B are greater than or equal to the preset transmission evaluation threshold, they are determined as initial data transmission channels. Further obtain the historical transmission information of these two initial data transmission channels in the past period of time (such as last week), and determine their historical evaluation values ​​(second evaluation values) based on this information. Calculate the difference between the first evaluation value of channel A and channel B and their respective second evaluation values ​​to obtain the evaluation deviation value. If the evaluation deviation value of channel A is less than or equal to the preset deviation value threshold, and the evaluation deviation value of channel B is greater than the preset deviation value threshold, then channel A is used as the target data transmission channel, and finally all compressed data packets are transmitted through channel A.

[0153] The beneficial effects of the above technical solution are: through grouping, compression, targeted extraction testing and selection of appropriate data transmission channels, the data transmission process can be optimized and the transmission efficiency can be improved; evaluation methods such as evaluation values ​​and deviation values ​​can be used to ensure that the selected target data transmission channel has good transmission performance and stability, thereby ensuring the quality of data transmission; and better transmission channels can be further screened out based on historical transmission information, so that transmission resources can be more reasonably allocated and utilized.

[0154] Example 8

[0155] The plurality of data groups are compressed to obtain a plurality of compressed data packets, including:

[0156] Take any data group as the target data group;

[0157] Binarizing the target data group to obtain a data length corresponding to the target data group;

[0158] Allocate and encode the data length of the target data group based on a preset ratio, and determine the encoding sequence number corresponding to the target data group;

[0159] Determine a coding table based on the data length of the target data group and the coding sequence number corresponding to the target data group;

[0160] Encode the target data group based on the encoding table to obtain encoding information corresponding to the target data group;

[0161] Based on the coding information, determining a coding matrix corresponding to the target data group;

[0162] Determining a data identifier of the target data group based on the encoding matrix;

[0163] Based on the data identifier, the target data group and the previous data group are aggregated and compressed to obtain a compressed data packet; each data group is traversed to obtain a plurality of compressed data packets.

[0164] In this embodiment, it is assumed that there are three data groups: Data1, Data2, and Data3. The length of each data group in binary form is: 100 bits, 150 bits, and 200 bits. The preset ratio for data length allocation can be simple (for example, 50% for direct encoding and 50% for determining the encoding strategy). The encoding table is a simple mapping table used to convert data length and encoding sequence number into specific encoding rules. Take any data group as the target data group. First, select one of the three data groups as the starting point, such as Data1. Binarize the target data group to obtain the data length; Data1 is already in binary form and its length is 100 bits. Allocate data length and encode to determine the encoding sequence number; assuming that the data length is allocated at a ratio of 50%, then 50 bits (i.e. half of 100 bits) are used for direct encoding or determining the encoding strategy. But for simplicity, a coding sequence number is determined directly based on the entire length (100 bits) and the preset encoding rule; the determined coding table is shown in Table 1:

[0165] Data length range Coding number Coding Rules 0-99 bits 0x01 Rule A 100-199 bits 0x02 Rule A 200+bits 0x03 Rule A

[0166] Table 1

[0167] In this example, the encoding sequence number of Data1 is 0x01, and the corresponding encoding rule is Rule A. Rule A is applied to encode Data1 to obtain encoding information; Rule A may be a fixed-length encoding rule.

[0168] In this embodiment, based on the coding information, the coding matrix corresponding to the target data group is determined, and each element in the coding information is mapped to a specific position of the matrix according to certain rules. For example, according to the order, type or other characteristics of the elements in the coding information, they are placed in different rows and columns of the matrix in sequence. Some conversion rules can be defined so that the coding information can be accurately reflected in the matrix. For example, different numerical values ​​or symbols are used to represent the positions of different coding elements in the matrix.

[0169] In this embodiment, the data identification of the target data group is determined based on the coding matrix, and some key features or patterns can be extracted from the coding matrix as data identification. For example, some statistics of the matrix (such as sum, mean, variance, etc.) are calculated, or the distribution of elements in a specific area of ​​the matrix is ​​observed. It is also possible to obtain a representative value or vector as a data identification by performing some transformation on the matrix (such as determinant calculation, eigenvector extraction, etc.). Alternatively, the data identification is determined according to a specific element combination or structure in the matrix using some predefined rules.

[0170] The beneficial effects of the above technical solution are: the amount of data is reduced through compression processing, saving storage space and transmission bandwidth; binarization processing and encoding help to represent data more accurately and efficiently, and improve the standardization and accuracy of data processing; preset proportion allocation and coding sequence determination can flexibly organize and manage data according to needs, enhancing the adaptability of data processing; coding tables and coding matrices make data coding and identification more systematic and orderly, facilitating subsequent data processing and analysis; data identification is used for aggregate compression to achieve targeted data combination and compression, and improve compression effect and efficiency.

[0171] Example 9

[0172] Determining a first evaluation value of each data transmission channel includes:

[0173]

[0174] Wherein, Q represents the first evaluation value of the data transmission channel; ln() represents the logarithmic function with the natural constant e as the base; n represents the total number of the tested compressed data packets; T ci represents the transmission delay when transmitting the i-th test compressed data packet; T bi represents the transmission delay of the i-th test compressed data packet; T0 represents the preset standard delay; τ i Indicates the length of the i-th test compressed data packet; t i represents the time consumed to transmit the i-th test compressed data packet; v represents the transmission rate of the data transmission channel; f represents the sending frequency of the test compressed data packet; f0 represents the sending frequency of the preset data packet; It represents the average bandwidth of transmitting several test compressed data packets; G0 represents the bandwidth of the data transmission channel.

[0175] The beneficial effects of the above technical solution are: it comprehensively considers multiple factors such as transmission delay, sending delay, data packet length, consumption time, transmission rate, sending frequency, average bandwidth, etc., and can evaluate the data transmission channel more comprehensively; through complex calculations such as logarithmic functions, it more accurately reflects the influence of various factors on channel evaluation, making the evaluation result more accurate; the first evaluation value obtained can be conveniently compared between different data transmission channels, which is helpful to select a better channel; problems existing in the data transmission channel can be discovered based on the evaluation value, such as excessive delay, insufficient bandwidth utilization, etc., thereby guiding targeted optimization and improvement of the channel.

[0176] To achieve the above purpose, if Figure 3 As shown, the second aspect of the present invention discloses a data resource sharing platform, including:

[0177] A receiving module, used for receiving data resource sharing request information sent by a data requester;

[0178] An analysis module, used to analyze the request information to obtain a target analysis result;

[0179] An evaluation module, used to obtain shared data resources based on the target analysis results and evaluate the shared data resources;

[0180] An acquisition module, used to acquire data transmission channel information for transmitting the shared data resource to the data requester when it is determined that the evaluation result is qualified;

[0181] The sharing module is used to transmit the shared data resources based on the data transmission channel to complete data resource sharing.

[0182] The beneficial effects of the above technical solution are: through a clear process, it can quickly respond to users' data resource sharing requests and reduce the time consumption of intermediate links; the analysis of request information helps to accurately understand the needs, so as to obtain shared data resources that better meet the requirements; the evaluation of shared data ensures the quality and reliability of the data and provides valuable data for the data requester; determines the qualified transmission channel to ensure the security and stability of the data during the transmission process; and can better integrate and utilize data resources, avoid resource waste, and improve the overall resource utilization efficiency.

[0183] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A data resource sharing method, characterized in that: include: Receiving data resource sharing request information sent by a data requester; Analyze the request information to obtain a target analysis result; Acquire shared data resources based on the target analysis results, and evaluate the shared data resources; When it is determined that the evaluation result is qualified, obtaining data transmission channel information for transmitting the shared data resource to the data requesting party; The shared data resource is transmitted based on the data transmission channel to complete data resource sharing.

2. The data resource sharing method according to claim 1, characterized in that: Analyze the request information to obtain target analysis results, including: Analyze the request information to determine the requester identity authentication information, data category information, data range information and data authority verification information; wherein the data category information corresponds to the data range information one-to-one, and the data range information corresponds to the data authority verification information one-to-one; Comparing the requester identity authentication information with a preset data resource sharing identity authentication table to determine a first analysis result; Compare the data category information with the preset data sharing category table to determine the target data category information; perform similarity calculation on the data range information corresponding to the data category information and the target data range information corresponding to the target data category information; when it is determined that the similarity is greater than or equal to the preset similarity threshold, obtain the target data authority verification information corresponding to the target data range information; compare the data authority verification information with the target data authority verification information to determine the second analysis result; Based on the first analysis result and the second analysis result, a target analysis result is determined.

3. The data resource sharing method according to claim 2, characterized in that: The shared data resource is evaluated, including: Evaluate each category of data in the shared data resource based on a preset data evaluation algorithm to obtain an evaluation value corresponding to each category of data; Traverse all category data and obtain several evaluation values; The average of the sum of several evaluation values ​​is taken as the evaluation value of the shared data resource.

4. The data resource sharing method according to claim 3, characterized in that: The preset data evaluation algorithm includes: Among them, P i represents the evaluation value of the i-th category data; n represents the total number of data categories in the shared data resource; ρ i Indicates the amount of data in the i-th category; q i represents the weight value of the i-th category data; T i，k represents the feature of the kth data in the i-th category data; F j Indicates the characteristic parameter of the jth byte in the shared data resource; m i Indicates the total number of bytes in the i-th category data of the shared data resource; Represents the mean of the type coefficient differences of shared data resources; r i Represents the type coefficient of the i-th category data; D i represents the data range of the i-th category data; d represents the mean of the data range in the request information; G represents the total range of the data in the request information.

5. The data resource sharing method according to claim 1, characterized in that: Before evaluating the shared data resource, it also includes: Clustering the shared data resources to obtain a plurality of shared sub-data groups; Take any shared sub-data group as the target data group; Obtaining a timestamp in a target data group; sorting the target data group based on the timestamp to obtain sequence data corresponding to the target data group; Segmenting the sequence data based on a preset step length to obtain a plurality of sequence sub-data; Performing anomaly detection on the plurality of sequence sub-data to obtain a plurality of initial abnormal sequence sub-data; Randomly select two initial abnormal sequence sub-data to obtain first abnormal sequence sub-data and second abnormal sequence sub-data; Calculate the correlation coefficient between each value in the first abnormal sequence sub-data and the value at the corresponding position in the second abnormal sequence sub-data; Deleting the corresponding value when the correlation coefficient is greater than or equal to the preset correlation threshold value, to obtain the first abnormal sequence sub-data after the value is deleted and the second abnormal sequence sub-data after the value is deleted; Traverse all the initial abnormal sequence sub-data to obtain several initial abnormal sequence sub-data after deleting values; The second similarities between the initial abnormal sequence sub-data after deleting the values ​​are calculated, and when it is determined that the maximum value of the second similarities is less than a preset similarity threshold, deduplication of the shared data resource is completed.

6. The data resource sharing method according to claim 5, characterized in that: Anomaly detection is performed on the plurality of sequence sub-data to obtain a plurality of initial abnormal sequence sub-data, including: Randomly select a sequence sub-data as the target sequence sub-data; respectively calculating first similarities between the target sequence sub-data and sequence sub-data other than the target sequence sub-data; Comparing the first similarity with a preset similarity threshold; When the first similarity is greater than or equal to a preset similarity threshold, the corresponding sequence sub-data is marked as abnormal; Traversing each sequence sub-data, and marking the corresponding sequence sub-data as abnormal when the first similarity is greater than or equal to a preset similarity threshold; Count the number of abnormal marks corresponding to each sequence sub-data; The sequence sub-data corresponding to the abnormal marking times being greater than or equal to the preset marking threshold is used as the initial abnormal sequence sub-data.

7. The data resource sharing method according to claim 4, characterized in that: Transmitting the shared data resource based on the data transmission channel includes: Dividing each category of data in the shared data resource into a plurality of data groups; compressing the plurality of data groups to obtain a plurality of compressed data packets; Extracting a preset ratio of the plurality of compressed data packets to obtain a plurality of test compressed data packets; Transmitting the plurality of test compressed data packets respectively based on the data transmission channels, and determining a first evaluation value of each data transmission channel; Comparing the first evaluation value with a preset transmission evaluation threshold; taking the data transmission channel corresponding to when the first evaluation value is greater than or equal to the preset transmission evaluation threshold as the initial data transmission channel, to obtain a plurality of initial data transmission channels; Acquire historical transmission information within a preset time period corresponding to the plurality of initial data transmission channels; Determine a historical evaluation value corresponding to the initial data transmission channel based on the historical transmission information to obtain a second evaluation value; Calculate the difference between the first evaluation value corresponding to each initial data transmission channel and the second evaluation value corresponding to each initial data transmission channel to obtain an evaluation deviation value; Comparing the evaluation deviation value with a preset deviation value threshold; The initial data transmission channel corresponding to when the evaluation deviation value is less than or equal to the preset deviation value threshold is used as the target data transmission channel; The plurality of compressed data packets are transmitted based on the target data transmission channel.

8. The data resource sharing method according to claim 7, characterized in that: The plurality of data groups are compressed to obtain a plurality of compressed data packets, including: Take any data group as the target data group; Binarizing the target data group to obtain a data length corresponding to the target data group; Allocate and encode the data length of the target data group based on a preset ratio, and determine the encoding sequence number corresponding to the target data group; Determine a coding table based on the data length of the target data group and the coding sequence number corresponding to the target data group; Encode the target data group based on the encoding table to obtain encoding information corresponding to the target data group; Based on the coding information, determining a coding matrix corresponding to the target data group; Determining a data identifier of the target data group based on the encoding matrix; Based on the data identifier, the target data group and the previous data group are aggregated and compressed to obtain a compressed data packet; each data group is traversed to obtain a plurality of compressed data packets.

9. The data resource sharing method according to claim 8, characterized in that: Determining a first evaluation value of each data transmission channel includes: Wherein, Q represents the first evaluation value of the data transmission channel; ln() represents the logarithmic function with the natural constant e as the base; n represents the total number of the tested compressed data packets; T ci represents the transmission delay when transmitting the i-th test compressed data packet; T bi represents the transmission delay of the i-th test compressed data packet; T0 represents the preset standard delay; τ i Indicates the length of the i-th test compressed data packet; t i represents the time consumed to transmit the i-th test compressed data packet; v represents the transmission rate of the data transmission channel; f represents the sending frequency of the test compressed data packet; f0 represents the sending frequency of the preset data packet; It represents the average bandwidth of transmitting several test compressed data packets; G0 represents the bandwidth of the data transmission channel.

10. A data resource sharing platform, characterized in that: include: A receiving module, used for receiving data resource sharing request information sent by a data requester; An analysis module, used to analyze the request information to obtain a target analysis result; An evaluation module, used to obtain shared data resources based on the target analysis results and evaluate the shared data resources; An acquisition module, used to acquire data transmission channel information for transmitting the shared data resource to the data requester when it is determined that the evaluation result is qualified; The sharing module is used to transmit the shared data resources based on the data transmission channel to complete data resource sharing.

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