A multi-dimensional data fusion driver performance intelligent evaluation method and system

Abstract

The application provides a kind of multi-dimensional data fusion's performance of official performance intelligent evaluation method and system, belongs to performance evaluation technical field, specifically includes: the data source except the associated data source is regarded as target data source, with the coincidence of target data source and associated data source, with the matching condition of the evaluation item of different associated deviation judicial personnel, determine the target data source of access performance evaluation system, with the data processing order of target data source and associated data source of access performance evaluation system as the basis, generate multiple performance evaluation schemes, based on the number of data sources required to verify and process the evaluation items of the personnel performance of different judicial personnel in different performance evaluation schemes, determine the switching processing order of performance evaluation scheme, and combine the identification result of manually input evaluation item, determine the evaluation processing result of different judicial personnel, improve the efficiency and reliability of performance evaluation processing.

Description

Technical Field

[0001] This invention belongs to the field of data evaluation technology, and in particular relates to a multi-dimensional data fusion intelligent evaluation method and system for judicial personnel performance. Background Technology

[0002] To achieve performance evaluation, existing technical solutions often rely on reading attendance data. However, these solutions inevitably cannot accurately determine the on-duty status of personnel, making it difficult to meet the accuracy requirements of the evaluation results.

[0003] Specifically, to address the aforementioned technical problems, invention patent application CN202211705481.7, "A Method and System for Monitoring and Analyzing the Status of Control Posts Based on Multiple Data Sources," utilizes monitoring devices to achieve dynamic, seamless, real-time, and intelligent monitoring of the status of control post personnel. This can provide auxiliary decision-making support for intelligent scheduling of control personnel, intelligent performance evaluation of controllers, scientific allocation of team resources, and intelligent formulation of training plans. However, the above technical solution has the following technical problems:

[0004] In the process of performance evaluation, it is necessary to combine multiple data sources, such as attendance systems, case filing systems, court hearing systems, monitoring systems, etc. If all data sources are connected to the performance evaluation system, the large amount of data to be processed will inevitably affect the stability of the performance evaluation system to a certain extent. Therefore, how to determine the type of data source to be connected and determine the performance evaluation processing scheme according to the type of data source to improve the efficiency of performance evaluation processing has become an urgent technical problem to be solved.

[0005] To address the aforementioned technical issues, this application provides a method and system for intelligent performance evaluation of judicial personnel based on multi-dimensional data fusion. Summary of the Invention

[0006] To achieve the objectives of this invention, the following technical solution is adopted:

[0007] Specifically, in the first aspect, this application provides a multi-dimensional data fusion-based intelligent performance evaluation method for judicial personnel, which specifically includes:

[0008] S1 determines the evaluation items for judicial personnel based on the personnel performance evaluation scheme, and determines the associated data sources in the data sources according to the correlation between different data sources and the evaluation items of different judicial personnel.

[0009] S2 connects the associated data source to the performance appraisal system. Based on the association between different associated data sources and the appraisal items of different judicial personnel, if the association deviation of judicial personnel does not meet the requirements, proceed to the next step.

[0010] S3 takes the data source other than the associated data source as the target data source, and determines the target data source to be accessed by the performance appraisal system based on the overlap between the target data source and the associated data source and the matching with the evaluation items of judicial personnel with different association deviations.

[0011] S4 generates multiple performance appraisal schemes based on the data processing order of the target data source and associated data source of the access performance appraisal system. Based on the number of data sources that need to be verified and processed for the personnel performance appraisal items of different judicial personnel in different performance appraisal schemes, the switching processing order of the performance appraisal schemes is determined. Combined with the identification results of manually input appraisal items, the appraisal processing results of different judicial personnel are determined.

[0012] The beneficial effects of this invention are as follows:

[0013] By considering the overlap between the target data source and related data sources, and the matching of evaluation items with different related deviation judicial personnel, the target data source for accessing the performance evaluation system is determined. This avoids the waste of access management resources of the performance evaluation platform caused by excessive duplication with related data sources, while also ensuring the completeness of the verification of evaluation items for related deviation judicial personnel and improving the efficiency of verification processing.

[0014] Based on the number of data sources that need to be verified and processed for the personnel performance evaluation items of different judicial personnel in different performance evaluation schemes, the switching processing order of the performance evaluation scheme is determined. This realizes the determination of the switching processing order of different performance evaluation schemes from the perspective of the number of data sources that different judicial personnel need to verify and process. This not only ensures the processing efficiency of performance evaluation, but also ensures that the performance evaluation scheme can be switched in a timely and effective manner when any data source has a call anomaly, thus ensuring the reliability of performance evaluation processing.

[0015] A further technical solution is that the evaluation items include case closure rate, mediation rate, appeal rate, enforcement rate, document completion status, and error status.

[0016] A further technical solution is that the method for determining the associated data source in the data source is as follows:

[0017] Based on the correlation between the data source and the evaluation items of different judicial personnel, determine the number of associated evaluation items for different data sources for different judicial personnel;

[0018] The correlation coefficient of the judicial personnel's evaluation items is determined based on the proportion of the number of related evaluation items to the total number of evaluation items for the judicial personnel.

[0019] Based on the correlation coefficients of different judicial personnel's evaluation items, it is determined whether the data source is a correlated data source.

[0020] A further technical solution is that when the number of judicial personnel whose correlation coefficient for evaluation items is greater than the preset threshold for correlation coefficient for evaluation items is within the preset range of the number of judicial personnel, the data source is determined to be a correlated data source.

[0021] A further technical solution is that the method for determining the associated data source in the data source is as follows:

[0022] Based on the correlation between the data source and the evaluation items of different judicial personnel, determine the number of associated evaluation items for different data sources for different judicial personnel;

[0023] Based on the number of related evaluation items for the judicial personnel, judicial personnel with related evaluation items are identified and designated as related judicial personnel.

[0024] Whether the data source is an associated data source is determined based on the proportion of the associated judicial personnel among the judicial personnel.

[0025] A further technical solution is that when the proportion of the associated judicial personnel among the judicial personnel is greater than the preset proportion of the associated judicial personnel, the data source is determined to be an associated data source.

[0026] A further technical solution is that the method for determining the switching order of the performance appraisal scheme is as follows:

[0027] The evaluation items for judicial personnel, excluding those manually input, are used as verification evaluation items. Based on the data sources corresponding to the verification evaluation items, the order of the data sources corresponding to different verification evaluation items in the performance evaluation scheme is determined.

[0028] Based on the order of the personnel performance verification evaluation items of different judicial personnel in the performance evaluation scheme, determine the verification quantity ratio of different judicial personnel's verification evaluation items when processing different data sources, and combine the order of different data sources in the performance evaluation scheme to determine the verification quantity ratio of judicial personnel's verification evaluation items under different verification data sources.

[0029] Based on the aforementioned order, the number of data sources that need to be processed when all the verification evaluation items of the judicial personnel's personnel performance are verified is determined, and this number is taken as the number of verification data sources for the judicial personnel. The switching processing order of the performance evaluation scheme is determined according to the number of verification data sources for different judicial personnel and the percentage of verification of the verification evaluation items for judicial personnel under different numbers of verification data sources.

[0030] A further technical solution involves determining the switching sequence of the performance evaluation scheme based on the number of verification data sources for different judicial personnel and the proportion of verification quantity for each verification evaluation item for judicial personnel under different numbers of verification data sources. Specifically, this includes:

[0031] The performance evaluation scheme in which the number of judicial personnel exceeds the preset threshold when the number of verified data sources is less than the preset number of data sources is used as an alternative evaluation scheme.

[0032] The matching evaluation scheme among the alternative evaluation schemes is determined by the percentage of verification items for judicial personnel with a preset number of verification data sources. The switching order of the matching evaluation scheme is determined by ranking the percentage of verification items for judicial personnel with a preset number of verification data sources from largest to smallest.

[0033] A further technical solution is that the matching evaluation scheme is an alternative evaluation scheme in which the average percentage of the verification quantity of the verification evaluation items of judicial personnel verifying the number of verification data sources under a preset value of the number of data sources is greater than a preset threshold for the percentage of verification quantity.

[0034] A further technical solution is that when the matching evaluation scheme has a data source with more than the preset failure number threshold, it automatically switches to the next matching evaluation scheme according to the switching processing order.

[0035] A further technical solution is that the method for determining the evaluation and handling results of the judicial personnel is as follows:

[0036] Based on the reading results of the judicial personnel's evaluation items from different data sources and the reading results of manually input evaluation items, the evaluation processing results of the judicial personnel are determined in accordance with the preset performance evaluation rules.

[0037] Secondly, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the aforementioned multi-dimensional data fusion intelligent performance evaluation method for judicial personnel.

[0038] Other features and advantages will be set forth in the following description, and the objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0039] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0040] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0041] Figure 1 This is a flowchart of a multi-dimensional data fusion-based intelligent performance evaluation method for judicial personnel.

[0042] Figure 2 It is a flowchart illustrating the method for determining the associated data sources within a data source.

[0043] Figure 3 This is a flowchart for determining whether the relevant deviation situation of judicial personnel does not meet the requirements;

[0044] Figure 4 This is a flowchart illustrating the method for determining the target data source for accessing the performance appraisal system. Detailed Implementation

[0045] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0046] In this application, by determining the performance plan for judicial personnel, the type of data source to be accessed through the performance appraisal platform is specifically identified, and a performance appraisal plan is generated based on the type of data source with the goal of improving the reliability and accuracy of performance evaluation.

[0047] Example 1

[0048] like Figure 1 As shown, this application provides a multi-dimensional data fusion-based intelligent performance evaluation method for judicial personnel, specifically including:

[0049] S1 determines the evaluation items for judicial personnel based on the personnel performance evaluation scheme, and determines the associated data sources in the data sources according to the correlation between different data sources and the evaluation items of different judicial personnel.

[0050] Furthermore, the evaluation items include case closure rate, mediation rate, appeal rate, enforcement rate, document completion status, and error status.

[0051] Specifically, such as Figure 2 As shown, the method for determining the associated data source in the data source is as follows:

[0052] Based on the correlation between the data source and the evaluation items of different judicial personnel, determine the number of associated evaluation items for different data sources for different judicial personnel;

[0053] The correlation coefficient of the judicial personnel's evaluation items is determined based on the proportion of the number of related evaluation items to the total number of evaluation items for the judicial personnel.

[0054] Based on the correlation coefficients of different judicial personnel's evaluation items, it is determined whether the data source is a correlated data source.

[0055] Furthermore, when the number of judicial personnel whose correlation coefficient for an evaluation item is greater than the preset threshold for the correlation coefficient for an evaluation item is within the preset range of the number of judicial personnel, the data source is determined to be a correlated data source.

[0056] Optionally, the method for determining the associated data source in the data source is as follows:

[0057] Based on the correlation between the data source and the evaluation items of different judicial personnel, determine the number of associated evaluation items for different data sources for different judicial personnel;

[0058] Based on the number of related evaluation items for the judicial personnel, judicial personnel with related evaluation items are identified and designated as related judicial personnel.

[0059] Whether the data source is an associated data source is determined based on the proportion of the associated judicial personnel among the judicial personnel.

[0060] Furthermore, when the proportion of the associated judicial personnel among the judicial personnel is greater than the preset proportion of the associated judicial personnel, the data source is determined to be an associated data source.

[0061] Optionally, the method for determining the associated data source in the data source is as follows:

[0062] S11 determines the number of associated evaluation items of different judicial personnel based on the correlation between the data source and the evaluation items of different judicial personnel. Based on the number of associated evaluation items of the judicial personnel, the judicial personnel with associated evaluation items are identified and regarded as associated judicial personnel. The judicial personnel correlation coefficient of the data source is determined according to the proportion of the associated judicial personnel among the judicial personnel.

[0063] S12 determines the evaluation correlation coefficient of different related judicial personnel based on the number of related evaluation items, the number of related information items that do not exist in other data sources, and the number of evaluation items.

[0064] S13 determines the comprehensive correlation coefficient of the data source by multiplying the correlation coefficient of judicial personnel in the data source with the average of the correlation coefficients of different related judicial personnel, and uses the comprehensive correlation coefficient to determine whether the data source is a related data source.

[0065] It should be noted that the comprehensive correlation coefficient of the data source ranges from 0 to 1. When the comprehensive correlation coefficient of the data source is greater than the preset data source correlation coefficient threshold, the data source is determined to be a correlated data source.

[0066] Optionally, step S11 above includes the following:

[0067] S111 determines the number of associated evaluation items of different judicial personnel based on the correlation between the data source and the evaluation items of different judicial personnel. When the sum of the number of associated evaluation items of different judicial personnel for the data source meets the requirements, the data source is determined to be an associated data source. When the sum of the number of associated evaluation items of different judicial personnel for the data source does not meet the requirements, proceed to step S112.

[0068] S112 Based on the number of related evaluation items of the judicial personnel, determine the judicial personnel with related evaluation items and regard them as related judicial personnel. According to the proportion of the related judicial personnel among the judicial personnel, determine the judicial personnel correlation coefficient of the data source. When the judicial personnel correlation coefficient of the data source is not less than the preset personnel correlation coefficient threshold, proceed to step S113. When the judicial personnel correlation coefficient of the data source is less than the preset personnel correlation coefficient threshold, determine that the data source does not belong to the related data source.

[0069] S113 When there are judicial personnel whose number of associated data sources exceeds the preset threshold for the number of associated data sources, proceed to step S114; when there are no judicial personnel whose number of associated data sources exceeds the preset threshold for the number of associated data sources, proceed to step S12.

[0070] S114 When the number of judicial personnel whose number of associated data sources exceeds the preset threshold for the number of associated data sources meets the requirements, the data source is determined to be an associated data source. When the number of judicial personnel whose number of associated data sources exceeds the preset threshold for the number of associated data sources does not meet the requirements, proceed to step S12.

[0071] Optionally, step S12 above includes the following:

[0072] S121 takes the related information items of different related judicial personnel that do not exist in other data sources as specific information items. When the number of specific information items of different related judicial personnel is greater than the preset threshold for the number of specific information items, the data source is determined to be a related data source. When the number of specific information items of different related judicial personnel is not greater than the preset threshold for the number of specific information items, proceed to step S122.

[0073] S122 Obtain the number of specific information items of different related judicial personnel. When there are related judicial personnel whose number of specific information items is greater than the threshold of the number of specific information items, proceed to step S123. When there are no related judicial personnel whose number of specific information items is greater than the threshold of the number of specific information items, proceed to step S124.

[0074] S123 When the number of associated judicial personnel whose number of specific information items is greater than the threshold of the number of specific information items meets the requirements, the data source is determined to be an associated data source. When the number of associated judicial personnel whose number of specific information items is greater than the threshold of the number of specific information items does not meet the requirements, proceed to step S124.

[0075] S124 determines the evaluation correlation coefficient of different related judicial personnel based on the number of related evaluation items, the number of related information items that do not exist in other data sources, and the number of evaluation items. When the average value of the evaluation correlation coefficient of different related judicial personnel is greater than the preset evaluation correlation coefficient threshold, the data source is determined to be a related data source. When the average value of the evaluation correlation coefficient of different related judicial personnel is not greater than the preset evaluation correlation coefficient threshold, proceed to step S13.

[0076] S2 connects the associated data source to the performance appraisal system. Based on the association between different associated data sources and the appraisal items of different judicial personnel, if the association deviation of judicial personnel does not meet the requirements, proceed to the next step.

[0077] Specifically, such as Figure 3 As shown, the determination of the related deviation of judicial personnel does not meet the requirements, specifically including:

[0078] By analyzing the correlation between different data sources and the evaluation items of different judicial personnel, we can identify judicial personnel whose evaluation items are not found in the aforementioned data sources.

[0079] Judicial personnel whose evaluation items are not in the associated data source are considered as judicial personnel with associated deviations.

[0080] Based on the proportion of judicial personnel with the aforementioned correlation deviation among all judicial personnel, it is determined whether the correlation deviation situation of the judicial personnel with the aforementioned correlation deviation meets the requirements.

[0081] Furthermore, if the proportion of judicial personnel with the aforementioned correlation deviation is greater than a preset threshold, then it is determined that the correlation deviation of the judicial personnel with the aforementioned correlation deviation does not meet the requirements.

[0082] It is understandable that when the correlation deviation of the personnel meets the requirements, there is no need to further determine the data source for accessing the performance appraisal system, and the performance appraisal scheme is generated based on the correlation data source.

[0083] Optionally, the determination of the related deviation of judicial personnel does not meet the requirements, specifically including:

[0084] By analyzing the correlation between different data sources and the evaluation items of different judicial personnel, we can identify judicial personnel whose evaluation items are not found in the aforementioned data sources.

[0085] Judicial personnel whose evaluation items are not in the associated data source are considered as judicial personnel with associated deviations.

[0086] The correlation deviation status of the judicial personnel with correlation deviation is determined based on the sum of the number of evaluation items that are not in the correlation data source.

[0087] Furthermore, when the sum of the number of evaluation items not in the relevant data source for different judicial personnel with correlation deviations is greater than the preset threshold for the number of deviation evaluation items, it is determined that the correlation deviation of the judicial personnel with correlation deviations does not meet the requirements.

[0088] Optionally, the determination of the related deviation of judicial personnel does not meet the requirements, specifically including:

[0089] S21 uses the correlation between different data sources and the evaluation items of different judicial personnel to identify judicial personnel whose evaluation items are not in the data sources, and identifies judicial personnel whose evaluation items are not in the data sources as judicial personnel with correlation deviations.

[0090] S22 determines the correlation deviation coefficient of judicial personnel with different correlation deviations based on the number of evaluation items not in the said correlation data source and the number of evaluation items among judicial personnel with different correlation deviations;

[0091] S23 determines the data source deviation amount based on the correlation deviation coefficient of different judicial personnel and the number of judicial personnel, and determines whether the correlation deviation of the judicial personnel meets the requirements based on the data source deviation amount.

[0092] Furthermore, when the deviation of the data source is greater than a preset deviation threshold, it is determined that the correlation deviation of the judicial personnel does not meet the requirements.

[0093] Optionally, step S21 above includes the following:

[0094] S211 uses the correlation between different data sources and the evaluation items of different judicial personnel to determine judicial personnel whose evaluation items are not in the data sources. Judicial personnel whose evaluation items are not in the data sources are identified as judicial personnel with correlation deviations. If the number of judicial personnel with correlation deviations or the proportion of such judicial personnel does not meet the requirements, then the correlation deviation of such judicial personnel is determined to be unsatisfactory. If the number of judicial personnel with correlation deviations or the proportion of such judicial personnel meets the requirements, then proceed to step S212.

[0095] S212 will use the evaluation items that are not in the associated data source as the associated deviation evaluation items. When the number of the associated deviation evaluation items does not meet the requirements, it will be determined that the associated deviation of the judicial personnel does not meet the requirements. When the number of the associated deviation evaluation items meets the requirements, the process will proceed to step S213.

[0096] S213 Obtain the proportion of the number of the associated deviation assessment items in the sum of the number of assessment items of the associated deviation judicial personnel, and determine the correlation deviation coefficient of the assessment items in combination with the number of the associated deviation assessment items. When the correlation deviation coefficient of the assessment items does not meet the requirements, it is determined that the correlation deviation of the associated deviation judicial personnel does not meet the requirements. When the correlation deviation coefficient of the assessment items meets the requirements, proceed to step S22.

[0097] Optionally, step S22 above includes the following:

[0098] S221 If there are no judicial personnel with related deviations whose number of related deviation evaluation items or whose proportion of related deviation evaluation items does not meet the requirements, then proceed to step S222. If there are judicial personnel with related deviations whose number of related deviation evaluation items or whose proportion of related deviation evaluation items does not meet the requirements, then proceed to step S223.

[0099] S222 When the correlation deviation coefficient of the assessment item is within the preset correlation deviation coefficient range, it is determined that the correlation deviation of the judicial personnel meets the requirements; when the correlation deviation coefficient of the assessment item is not within the preset correlation deviation coefficient range, proceed to step S224.

[0100] S223 When the number of related deviation evaluation items or the number of related deviation evaluation items does not meet the requirement of the proportion of the number of evaluation items of the related deviation judicial personnel is greater than the threshold of the number of deviation personnel, it is determined that the related deviation situation of the related deviation judicial personnel does not meet the requirements. When the number of related deviation evaluation items or the number of related deviation judicial personnel does not meet the requirement of the proportion of the number of evaluation items of the related deviation judicial personnel is not greater than the threshold of the number of deviation personnel, proceed to step S224.

[0101] S224 determines the correlation deviation coefficient of judicial personnel with different correlation deviations based on the number of evaluation items not in the correlation data source and the number of evaluation items. When the sum of the correlation deviation coefficients of judicial personnel with different correlation deviations does not meet the requirements, it is determined that the correlation deviation of the judicial personnel with different correlation deviations does not meet the requirements. When the sum of the correlation deviation coefficients of judicial personnel with different correlation deviations meets the requirements, the process proceeds to step S23.

[0102] S3 takes the data source other than the associated data source as the target data source, and determines the target data source to be accessed by the performance appraisal system based on the overlap between the target data source and the associated data source and the matching with the evaluation items of judicial personnel with different association deviations.

[0103] Specifically, such as Figure 4 As shown, the method for determining the target data source for accessing the performance appraisal system is as follows:

[0104] Based on the overlap between the target data source and the associated data source, determine the number of overlaps with different associated data sources in the evaluation items of different judicial personnel, and use this as the number of information item overlaps.

[0105] The evaluation items of judicial personnel with the aforementioned correlation deviations who are not in the associated data source are used as the matching deviation evaluation items. The number of deviation matches is determined based on the number of matches of the matching deviation evaluation items with different judicial personnel with correlation deviations.

[0106] Based on the ratio of the number of deviation matches to the number of information item overlaps, the data source matching coefficient of the target data source is determined, and based on the data source matching coefficient, it is determined whether the target data source is a target data source for accessing the performance appraisal system.

[0107] Furthermore, determining whether the target data source is a target data source for accessing the performance appraisal system based on the data source matching coefficient specifically includes:

[0108] Based on the data source matching coefficient, the access processing order of different target data sources is determined;

[0109] Based on the access processing order, multiple access schemes are formed according to the number of accesses to the target data source;

[0110] For specific examples, if there are target data sources A, B, and C, and the access processing order is A, B, C, then the resulting access schemes are A, A and B, and A, B, and C.

[0111] Using the constraint that the proportion of evaluation items for judicial personnel with different correlation deviations in data sources all exceed a preset proportion threshold, the access scheme with the fewest accesses is selected as the target access scheme. Based on whether the target data source is in the target access scheme, it is determined whether the target data source is the target data source for accessing the performance evaluation system.

[0112] It should be noted that when the target data source is in the target access scheme, the target data source is determined to be the target data source for accessing the performance evaluation system.

[0113] Optionally, the method for determining the target data source for accessing the performance appraisal system is as follows:

[0114] The evaluation items of judicial personnel with the aforementioned correlation deviation that are not in the associated data source are used as the matching deviation evaluation items. The number of deviation matching items is determined based on the number of matching deviation evaluation items with different judicial personnel with the correlation deviation. When the proportion of the number of deviation matching items in the number of matching deviation evaluation items with different judicial personnel with the correlation deviation is less than the preset proportion of the number of deviations, it is determined that the target data source does not belong to the target data source accessing the performance evaluation system.

[0115] When the proportion of the number of deviation matches in the assessment items of judicial personnel with different associated deviations is not less than the preset proportion of deviations:

[0116] Obtain the number of deviation matches among judicial personnel with different correlation deviations, and determine the deviation correlation coefficient with judicial personnel with different correlation deviations based on the proportion of the number of deviation matches in the matching deviation evaluation item;

[0117] When the average value of the deviation correlation coefficients of judicial personnel with different correlation deviations does not meet the requirements, it is determined that the target data source does not belong to the target data source accessing the performance evaluation system.

[0118] When the average value of the deviation correlation coefficients of judicial personnel with different correlation deviations meets the requirements:

[0119] Based on the deviation correlation coefficient, the number of judicial personnel with correlation deviation whose deviation correlation coefficient is less than the preset deviation correlation coefficient threshold is determined. When the number of judicial personnel with correlation deviation whose deviation correlation coefficient is less than the preset deviation correlation coefficient threshold does not meet the requirements, it is determined that the target data source does not belong to the target data source accessing the performance evaluation system.

[0120] When the number of judicial personnel with correlated deviations that are less than the preset correlation coefficient threshold meets the requirements:

[0121] Based on the overlap between the target data source and the associated data source, determine the number of overlaps with different associated data sources in the evaluation items of different judicial personnel, and use this as the number of information item overlaps.

[0122] Based on the ratio of the number of deviation matches to the number of information item overlaps, the data source matching coefficient of the target data source is determined, and based on the data source matching coefficient, it is determined whether the target data source is a target data source for accessing the performance appraisal system.

[0123] S4 generates multiple performance appraisal schemes based on the data processing order of the target data source and associated data source of the access performance appraisal system. Based on the number of data sources that need to be verified and processed for the personnel performance appraisal items of different judicial personnel in different performance appraisal schemes, the switching processing order of the performance appraisal schemes is determined. Combined with the identification results of manually input appraisal items, the appraisal processing results of different judicial personnel are determined.

[0124] Specifically, the method for determining the switching order of the performance appraisal scheme is as follows:

[0125] The evaluation items for judicial personnel, excluding those manually input, are used as verification evaluation items. Based on the data sources corresponding to the verification evaluation items, the order of the data sources corresponding to different verification evaluation items in the performance evaluation scheme is determined.

[0126] Based on the order of the personnel performance verification evaluation items of different judicial personnel in the performance evaluation scheme, determine the verification quantity ratio of different judicial personnel's verification evaluation items when processing different data sources, and combine the order of different data sources in the performance evaluation scheme to determine the verification quantity ratio of judicial personnel's verification evaluation items under different verification data sources.

[0127] Based on the aforementioned order, the number of data sources that need to be processed when all the verification evaluation items of the judicial personnel's personnel performance are verified is determined, and this number is taken as the number of verification data sources for the judicial personnel. The switching processing order of the performance evaluation scheme is determined according to the number of verification data sources for different judicial personnel and the percentage of verification of the verification evaluation items for judicial personnel under different numbers of verification data sources.

[0128] Furthermore, based on the number of verification data sources for different judicial personnel and the percentage of verification items for judicial personnel under different numbers of verification data sources, the switching processing order of the performance evaluation scheme is determined, specifically including:

[0129] The performance evaluation scheme in which the number of judicial personnel exceeds the preset threshold when the number of verified data sources is less than the preset number of data sources is used as an alternative evaluation scheme.

[0130] The matching evaluation scheme among the alternative evaluation schemes is determined by the percentage of verification items for judicial personnel with a preset number of verification data sources. The switching order of the matching evaluation scheme is determined by ranking the percentage of verification items for judicial personnel with a preset number of verification data sources from largest to smallest.

[0131] It is understood that the matching evaluation scheme is an alternative evaluation scheme in which the average percentage of the verification quantity of the verification evaluation items of judicial personnel verifying the number of verification data sources under the preset value of the number of data sources is greater than the preset threshold of the percentage of the number of verifications.

[0132] It should be noted that when the matching evaluation scheme has a data source with more than the preset failure count threshold, it will automatically switch to the next matching evaluation scheme according to the switching processing order.

[0133] Furthermore, the method for determining the evaluation and handling results of the judicial personnel is as follows:

[0134] Based on the reading results of the judicial personnel's evaluation items from different data sources and the reading results of manually input evaluation items, the evaluation processing results of the judicial personnel are determined in accordance with the preset performance evaluation rules.

[0135] Example 2

[0136] Secondly, the present invention provides a computer system comprising: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the aforementioned multi-dimensional data fusion intelligent performance evaluation method for judicial personnel.

[0137] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0138] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0139] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A multi-dimensional data fusion-based intelligent performance evaluation method for judicial personnel, characterized in that, Specifically, it includes: The evaluation items for judicial personnel are determined based on the personnel performance evaluation scheme. The associated data sources are determined according to the correlation between different data sources and the evaluation items of different judicial personnel. Connect the associated data sources to the performance appraisal system. Based on the correlation between different associated data sources and the appraisal items of different judicial personnel, determine the correlation deviation. If the correlation deviation of judicial personnel does not meet the requirements, proceed to the next step. The target data source is determined by taking the data source other than the associated data source as the target data source, and by the overlap between the target data source and the associated data source, and the matching between the target data source and the evaluation items of judicial personnel with different correlation deviations. Based on the data processing order of the target data source and associated data source of the access performance appraisal system, multiple performance appraisal schemes are generated. Based on the number of data sources that need to be verified and processed for the personnel performance appraisal items of different judicial personnel in different performance appraisal schemes, the switching processing order of the performance appraisal schemes is determined. Combined with the identification results of manually input appraisal items, the appraisal processing results of different judicial personnel are determined. The method for determining the associated data source in the data source is as follows: Based on the correlation between the data source and the evaluation items of different judicial personnel, determine the number of associated evaluation items for different data sources for different judicial personnel; The correlation coefficient of the judicial personnel's evaluation items is determined based on the proportion of the number of related evaluation items to the total number of evaluation items for the judicial personnel. Based on the correlation coefficients of different judicial personnel's evaluation items, it is determined whether the data source is a correlated data source.

2. The intelligent performance evaluation method for judicial personnel based on multi-dimensional data fusion as described in claim 1, characterized in that, The evaluation criteria include case closure rate, mediation rate, appeal rate, enforcement rate, document completion status, and error rate.

3. The intelligent performance evaluation method for judicial personnel based on multi-dimensional data fusion as described in claim 1, characterized in that, When the number of judicial personnel whose correlation coefficient for an evaluation item is greater than the preset threshold for the correlation coefficient for an evaluation item is within the preset range of the number of judicial personnel, the data source is determined to be a correlated data source.

4. The intelligent performance evaluation method for judicial personnel based on multi-dimensional data fusion as described in claim 1, characterized in that, The determination of related deviations by judicial personnel does not meet the requirements, specifically including: By analyzing the correlation between different data sources and the evaluation items of different judicial personnel, we can identify judicial personnel whose evaluation items are not found in the aforementioned data sources. Judicial personnel whose evaluation items are not in the associated data source are considered as judicial personnel with associated deviations. Based on the proportion of judicial personnel with the aforementioned correlation deviation among all judicial personnel, it is determined whether the correlation deviation situation of the judicial personnel with the aforementioned correlation deviation meets the requirements.

5. The intelligent performance evaluation method for judicial personnel based on multi-dimensional data fusion as described in claim 4, characterized in that, When the correlation deviation of the judicial personnel meets the requirements, there is no need to further determine the data source for accessing the performance appraisal system, and the performance appraisal scheme is generated based on the correlation data source.

6. The intelligent performance evaluation method for judicial personnel based on multi-dimensional data fusion as described in claim 1, characterized in that, The method for determining the switching order of the performance appraisal scheme is as follows: The evaluation items for judicial personnel, excluding those manually input, are used as verification evaluation items. Based on the data sources corresponding to the verification evaluation items, the order of the data sources corresponding to different verification evaluation items in the performance evaluation scheme is determined. Based on the order of the personnel performance verification evaluation items of different judicial personnel in the performance evaluation scheme, determine the verification quantity ratio of different judicial personnel's verification evaluation items when processing different data sources, and combine the order of different data sources in the performance evaluation scheme to determine the verification quantity ratio of judicial personnel's verification evaluation items under different verification data sources. Based on the aforementioned order, the number of data sources that need to be processed when all the verification evaluation items of the judicial personnel's personnel performance are verified is determined, and this number is taken as the number of verification data sources for the judicial personnel. The switching processing order of the performance evaluation scheme is determined according to the number of verification data sources for different judicial personnel and the percentage of verification of the verification evaluation items for judicial personnel under different numbers of verification data sources.

7. The intelligent performance evaluation method for judicial personnel based on multi-dimensional data fusion as described in claim 6, characterized in that, Based on the number of verification data sources for different judicial personnel and the percentage of verification items for judicial personnel under different numbers of verification data sources, the switching process order of the performance appraisal scheme is determined, specifically including: The performance evaluation scheme in which the number of judicial personnel exceeds the preset threshold when the number of verified data sources is less than the preset number of data sources is used as an alternative evaluation scheme. The matching evaluation scheme among the alternative evaluation schemes is determined by the percentage of verification items for judicial personnel with a preset number of verification data sources. The switching order of the matching evaluation scheme is determined by ranking the percentage of verification items for judicial personnel with a preset number of verification data sources from largest to smallest.

8. The intelligent performance evaluation method for judicial personnel based on multi-dimensional data fusion as described in claim 7, characterized in that, The matching evaluation scheme is an alternative evaluation scheme in which the average percentage of the verification quantity of judicial personnel verifying the number of data sources is greater than the preset threshold for the percentage of verification quantity, given a preset value for the number of data sources.

9. A computer system, comprising: A memory and processor connected by communication, and a computer program stored on the memory and capable of running on the processor, characterized in that, when the processor runs the computer program, it executes a multi-dimensional data fusion intelligent performance evaluation method for judicial personnel as described in any one of claims 1-8.

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