Intelligent judicial personnel performance evaluation method and system based on multi-dimensional data fusion

Abstract

The invention provides an intelligent judicial personnel performance evaluation method and system based on multi-dimensional data fusion, and belongs to the technical field of performance evaluation. Determining the target data source accessed to the performance evaluation system according to the coincidence condition of the target data source and the associated data source and the matching condition of evaluation items of different associated deviation judicial officers, and generating a plurality of performance evaluation schemes on the basis of the data processing sequence of the target data source accessed to the performance evaluation system and the associated data source, based on the number of data sources needing to be verified and processed for evaluation items of personnel performance of different judicial officers in different performance evaluation schemes, a switching processing sequence of the performance evaluation schemes is determined, and evaluation processing results of different judicial officers are determined in combination with an identification result of the evaluation items input manually. And the efficiency and reliability of performance evaluation processing are improved.

Description

Technical Field

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

[0002] In order to realize the assessment and processing of personnel performance, the existing technical solutions often use the reading of attendance data to evaluate and process personnel performance. However, the above technical solutions inevitably cannot accurately determine the on-the-job status of personnel, making it difficult to meet the accuracy of the evaluation results.

[0003] Specifically, to solve the above technical problems, the invention patent application CN202211705481.7 "A method and system for monitoring and analyzing the status of control post based on multiple data sources" uses a monitoring device to achieve dynamic, non-sensing, real-time, and intelligent monitoring of the status of control post personnel. It can provide auxiliary decision-making for intelligent control scheduling, intelligent evaluation of controller performance, scientific matching 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 for performance evaluation, such as attendance system, case filing system, trial system, monitoring system, etc. If all data sources are connected to the performance evaluation system, due to the large amount of data processed, it will inevitably cause the operational stability of the performance evaluation system to be affected to a certain extent. Therefore, how to determine the type of data source to be connected, and determine the performance evaluation processing plan based on the type of data source to be connected, and improve the efficiency of performance evaluation processing has become a technical problem that needs to be solved urgently.

[0005] In order to solve the above technical problems, this application provides a method and system for intelligent evaluation of judicial personnel performance based on multi-dimensional data fusion. Summary of the Invention

[0006] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

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

[0008] S1 determines the evaluation items of the judicial personnel based on the evaluation plan of the judicial personnel's personnel performance, and determines the associated data sources among the data sources according to the association between different data sources and the evaluation items of different judicial personnel;

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

[0010] S3: The data source other than the associated data source is used as the target data source, and the target data source to be connected to the performance evaluation system is determined based on the overlap between the target data source and the associated data source and the matching between the evaluation items of judicial personnel with different associated deviations;

[0011] S4 generates multiple performance evaluation plans based on the data processing order of the target data source and the associated data source connected to the performance evaluation system, determines the switching processing order of the performance evaluation plan based on the number of data sources that need to be verified and processed for the evaluation items of the personnel performance of different judicial personnel in different performance evaluation plans, and determines the evaluation processing results of different judicial personnel in combination with the recognition results of the manually input evaluation items.

[0012] The beneficial effects of the present invention are:

[0013] The target data source for accessing the performance evaluation system is determined based on the overlap between the target data source and the associated data source, and the matching with the evaluation items of different associated deviation judicial personnel. This not only avoids the waste of access management resources of the performance evaluation platform caused by a large number of duplications with the associated data sources, but also ensures the verification completeness of the evaluation items of associated deviation judicial personnel, and improves the efficiency of verification processing.

[0014] Based on the number of data sources that need to be verified and processed for the evaluation items of the personnel performance of different judicial personnel in different performance evaluation plans, the switching processing order of the performance evaluation plans is determined, thereby realizing the determination of the switching processing order of different performance evaluation plans from the perspective of the number of data sources that need to be verified and processed for different judicial personnel. This not only ensures the processing efficiency of the performance evaluation, but also ensures that when there is a call exception in any data source, the performance evaluation plan can be switched in a timely and effective manner, thereby ensuring the reliability of the performance evaluation processing.

[0015] A further technical solution is that the evaluation items include case closing rate, mediation rate, appeal rate, execution 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:

[0017] Determining the number of evaluation items associated with different judicial personnel for different data sources based on the association between the data sources and the evaluation items of different judicial personnel;

[0018] Determining a correlation coefficient of the judicial personnel's evaluation items based on the proportion of the number of the judicial personnel's related evaluation items to the number of the judicial personnel's evaluation items;

[0019] According to the correlation coefficients of the evaluation items of different judicial personnel, it is determined whether the data source is a correlated data source.

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

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

[0022] Determining the number of evaluation items associated with different judicial personnel for different data sources based on the association between the data sources and the evaluation items of different judicial personnel;

[0023] Based on the number of related evaluation items of the judicial personnel, determining the judicial personnel with related evaluation items and treating them 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 number of the related judicial personnel among the judicial personnel is greater than the proportion of the preset number of related judicial personnel, the data source is determined to be a related data source.

[0026] A further technical solution is that the method for determining the switching processing order of the performance evaluation scheme is:

[0027] using the evaluation items of the judicial personnel excluding manual input as verification evaluation items, and determining the order of the data sources corresponding to different verification evaluation items in the performance evaluation plan based on the data sources corresponding to the verification evaluation items;

[0028] Based on the order of the verification and evaluation items of the personnel performance of different judicial personnel in the performance evaluation plan, determine the proportion of the verification quantity of the verification and evaluation items of different judicial personnel when different data sources are processed, and based on the order of different data sources in the performance evaluation plan, determine the proportion of the verification quantity of the verification and evaluation items of judicial personnel under different numbers of verification data sources;

[0029] Based on the said order, when all the verification and evaluation items of the personnel performance of the judicial personnel are verified and processed, the number of data sources that need to be processed is determined, and it is used as the number of verification data sources for the judicial personnel. According to the number of verification data sources of different judicial personnel and the proportion of the verification number of verification evaluation items of judicial personnel under different numbers of verification data sources, the switching processing order of the performance evaluation plan is determined.

[0030] A further technical solution is to determine the switching processing order of the performance evaluation scheme according to the number of verification data sources of different judicial personnel and the verification number ratio of the verification evaluation items of judicial personnel under different numbers of verification data sources, specifically including:

[0031] The performance evaluation scheme in which the number of judicial personnel is greater than the preset personnel number threshold when the number of verification data sources is less than the preset value of the number of data sources is used as an alternative evaluation scheme;

[0032] The matching evaluation scheme in the alternative evaluation scheme is determined based on the proportion of the verification number of evaluation items of judicial personnel who verify the number of data sources under the preset value of the number of data sources, and the switching processing order of the matching evaluation scheme is determined based on the average value of the proportion of the verification number of evaluation items of judicial personnel who verify the number of data sources under the preset value of the number of data sources from large to small.

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

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

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

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

[0037] In a second aspect, the present invention provides a computer system comprising: a memory and a processor in communication connection, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned intelligent evaluation method of judicial personnel performance based on multi-dimensional data fusion when running the computer program.

[0038] Other features and advantages will be described in the following description. The objectives and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0039] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the accompanying drawings.

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

[0042] Figure 2 is a flow chart of a method for determining an associated data source in a data source;

[0043] Figure 3 It is a flow chart to determine the correlation deviation of judicial personnel who do not meet the requirements;

[0044] Figure 4 It is a flow chart of a method for determining a target data source for accessing a performance evaluation system. DETAILED DESCRIPTION

[0045] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this specification without creative work should fall within the scope of protection of this specification.

[0046] In this application, by determining the performance plan of judicial personnel, the type of data source connected to the performance evaluation platform is determined in a targeted manner, and based on the type of data source, a performance evaluation plan is generated 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 method for intelligent evaluation of judicial personnel performance, which specifically includes:

[0049] S1 determines the evaluation items of the judicial personnel based on the evaluation plan of the judicial personnel's personnel performance, and determines the associated data sources among the data sources according to the association 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, execution 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:

[0052] Determining the number of evaluation items associated with different judicial personnel for different data sources based on the association between the data sources and the evaluation items of different judicial personnel;

[0053] Determining a correlation coefficient of the judicial personnel's evaluation items based on the proportion of the number of the judicial personnel's related evaluation items to the number of the judicial personnel's evaluation items;

[0054] According to the correlation coefficients of the evaluation items of different judicial personnel, it is determined whether the data source is a correlated data source.

[0055] Furthermore, when the number of judicial personnel whose evaluation item correlation coefficient is greater than a preset evaluation item correlation coefficient threshold is within a preset judicial personnel number range, 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:

[0057] Determining the number of evaluation items associated with different judicial personnel for different data sources based on the association between the data sources and the evaluation items of different judicial personnel;

[0058] Based on the number of related evaluation items of the judicial personnel, determining the judicial personnel with related evaluation items and treating them 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 number of the associated judicial personnel among the judicial personnel is greater than the proportion of the preset number of 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:

[0062] S11 determines the number of associated evaluation items of different judicial personnel from different data sources based on the association between the data sources and the evaluation items of different judicial personnel. Based on the number of associated evaluation items of the judicial personnel, determines the judicial personnel with associated evaluation items and uses them as associated judicial personnel. Determines the judicial personnel association coefficient of the data source based on the proportion of the associated judicial personnel among the judicial personnel.

[0063] S12 determines the evaluation correlation coefficients of different related judicial personnel based on the number of related evaluation items of the different related judicial personnel, 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 based on the product of the judicial personnel correlation coefficient of the data source and the average value of the evaluation 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, wherein when the comprehensive correlation coefficient of the data source is greater than a preset data source correlation coefficient threshold, the data source is determined to be a correlated data source.

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

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

[0068] S112 determines the judicial personnel with associated evaluation items based on the number of associated evaluation items of the judicial personnel, and uses them as associated judicial personnel. According to the proportion of the associated judicial personnel among the judicial personnel, the judicial personnel association coefficient of the data source is determined. When the judicial personnel association coefficient of the data source is not less than the preset personnel association coefficient threshold, the process proceeds to step S113. When the judicial personnel association coefficient of the data source is less than the preset personnel association coefficient threshold, the data source is determined not to be an associated data source.

[0069] S113: If there are judicial personnel whose number of associated data sources is greater than the preset threshold value of associated data sources, the process proceeds to step S114; if there are no judicial personnel whose number of associated data sources is greater than the preset threshold value of associated data sources, the process proceeds to step S12;

[0070] S114 When the number of judicial personnel whose number of associated data sources is greater than the preset threshold of the number of associated data sources meets the requirements, it is determined that the data source belongs to an associated data source; when the number of judicial personnel whose number of associated data sources is greater than the preset threshold of the number of associated data sources does not meet the requirements, proceed to step S12.

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

[0072] S121: The associated information items of different associated judicial personnel that do not exist in other data sources are regarded as specific information items. When the number of specific information items of different associated judicial personnel is greater than a preset threshold number of specific information items, it is determined that the data source belongs to an associated data source. When the number of specific information items of different associated judicial personnel is not greater than the preset threshold number of specific information items, the process proceeds to step S122.

[0073] S122 obtains the number of specific information items of different associated judicial personnel. If there is an associated judicial personnel whose number of specific information items is greater than the threshold number of specific information items, the process proceeds to step S123. If there is no associated judicial personnel whose number of specific information items is greater than the threshold number of specific information items, the process proceeds to step S124.

[0074] S123: When the number of specific information items is greater than the threshold number of specific information items, and the number of associated judicial personnel meets the requirement, it is determined that the data source belongs to the associated data source; when the number of specific information items is greater than the threshold number of specific information items, and the number of associated judicial personnel does not meet the requirement, the process proceeds to step S124;

[0075] S124 determines the evaluation correlation coefficients of different associated judicial personnel based on the number of associated evaluation items of different associated judicial personnel, the number of associated information items that do not exist in other data sources, and the number of evaluation items. When the average value of the evaluation correlation coefficients of different associated judicial personnel is greater than the preset evaluation correlation coefficient threshold, it is determined that the data source belongs to an associated data source. When the average value of the evaluation correlation coefficients of different associated 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 evaluation system, and determines the association deviation based on the association between different associated data sources and the evaluation items of different judicial personnel. If the association deviation of the judicial personnel does not meet the requirements, proceed to the next step;

[0077] Specifically, such as Figure 3 As shown in the figure, the related deviation of judicial personnel determined to be related deviation does not meet the requirements, including:

[0078] Based on the association between different related data sources and the evaluation items of different judicial personnel, determine the judicial personnel whose evaluation items are not in the related data sources;

[0079] Judicial personnel with evaluation items that are not in the associated data source are regarded as associated deviation judicial personnel;

[0080] According to the proportion of the judicial personnel with correlation deviation among the judicial personnel, determine whether the correlation deviation situation of the judicial personnel with correlation deviation meets the requirements.

[0081] Furthermore, when the proportion of the number of judicial personnel with associated deviations among the judicial personnel is greater than a preset number proportion threshold, it is determined that the associated deviation situation of the judicial personnel with associated deviations does not meet the requirements.

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

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

[0084] Based on the association between different related data sources and the evaluation items of different judicial personnel, determine the judicial personnel whose evaluation items are not in the related data sources;

[0085] Judicial personnel with evaluation items that are not in the associated data source are regarded as associated deviation judicial personnel;

[0086] Whether the correlation deviation situation of the correlation deviation judicial personnel meets the requirements is determined based on the sum of the number of evaluation items of the correlation deviation judicial personnel that are not in the correlation data source.

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

[0088] Optionally, the determination of the associated bias judicial personnel's associated bias situation does not meet the requirements, specifically including:

[0089] S21 determines, based on the association between different related data sources and the evaluation items of different judicial personnel, judicial personnel with evaluation items not in the related data sources, and regards the judicial personnel with evaluation items not in the related data sources as judicial personnel with association deviations;

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

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

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

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

[0094] S211 determines the judicial personnel with evaluation items that are not in the associated data source based on the association between different associated data sources and different judicial personnel. The judicial personnel with evaluation items that are not in the associated data source are regarded as associated deviation judicial personnel. When the number of the associated deviation judicial personnel or the proportion of the number of the judicial personnel does not meet the requirements, it is determined that the associated deviation of the associated deviation judicial personnel does not meet the requirements. When the number of the associated deviation judicial personnel or the proportion of the number of the judicial personnel do meet the requirements, the process proceeds to step S212.

[0095] S212: The evaluation items that are not in the associated data source are used as associated deviation evaluation items. When the number of the associated deviation evaluation items does not meet the requirement, it is determined that the associated deviation of the associated deviation judicial personnel does not meet the requirement. When the number of the associated deviation evaluation items meets the requirement, the process proceeds to step S213.

[0096] S213 obtains the proportion of the number of the associated deviation evaluation items in the sum of the number of evaluation items of the associated deviation judicial personnel, and determines the evaluation item associated deviation coefficient in combination with the number of associated deviation evaluation items. When the evaluation item associated deviation coefficient does not meet the requirements, it is determined that the associated deviation situation of the associated deviation judicial personnel does not meet the requirements. When the evaluation item associated deviation coefficient meets the requirements, it proceeds to step S22.

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

[0098] S221 determines, based on the number of related deviation evaluation items of different related deviation judicial personnel and the proportion of related deviation evaluation items in the number of evaluation items of the related deviation judicial personnel, that there is no related deviation judicial personnel whose number of related deviation evaluation items and the proportion of related deviation evaluation items in the number of evaluation items of the related deviation judicial personnel do not meet the requirements, then proceeds to step S222; when there is a related deviation judicial personnel whose number of related deviation evaluation items or the proportion of related deviation evaluation items in the number of evaluation items of the related deviation judicial personnel do not meet the requirements, then proceeds to step S223;

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

[0100] S223: When the number of associated deviation evaluation items or the proportion of associated deviation evaluation items in the number of evaluation items of the associated deviation judicial personnel whose number does not meet the requirement is greater than the deviation personnel number threshold, it is determined that the associated deviation situation of the associated deviation judicial personnel does not meet the requirement; when the number of associated deviation evaluation items or the proportion of associated deviation evaluation items in the number of evaluation items of the associated deviation judicial personnel whose number does not meet the requirement is not greater than the deviation personnel number threshold, the process proceeds to step S224;

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

[0102] S3: The data source other than the associated data source is used as the target data source, and the target data source to be connected to the performance evaluation system is determined based on the overlap between the target data source and the associated data source and the matching between the evaluation items of judicial personnel with different associated deviations;

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

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

[0105] Using the evaluation item of the associated deviation judicial personnel that is not in the associated data source as the matching deviation evaluation item, and determining the number of deviation matches based on the number of matches with the matching deviation evaluation items of different associated deviation judicial personnel;

[0106] Based on the ratio of the number of deviation matches to the number of overlapping information items, 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 the target data source for accessing the performance evaluation system.

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

[0108] Determining the access processing order of different target data sources based on the data source matching coefficient;

[0109] Based on the access processing sequence, forming multiple access plans according to the access quantity of the target data source;

[0110] To give a specific example, if there are target data sources A, B, and C, and the access processing order is A, B, and C, then the access solutions obtained are A, A and B, and A, B, and C.

[0111] Taking the constraint condition that the proportion of evaluation items of judicial personnel with different correlation deviations in the data source is greater than the preset proportion threshold, the access plan with the least number of accesses is taken as the target access plan, and whether the target data source is the target data source for accessing the performance evaluation system is determined based on whether the target data source is in the target access plan.

[0112] It should be noted that, when the target data source is in the target access solution, 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 evaluation system is:

[0114] The evaluation item of the associated deviation judicial personnel that is not in the associated data source is used as the matching deviation evaluation item, and the deviation matching number is determined according to the matching number of the matching deviation evaluation items of different associated deviation judicial personnel. When the proportion of the deviation matching number in the number of matching deviation evaluation items of different associated deviation judicial personnel is less than the preset deviation number proportion, it is determined that the target data source does not belong to the target data source for accessing the performance evaluation system;

[0115] When the number of deviation matches accounts for no less than the preset deviation number in the number of matching deviation evaluation items of different associated deviation judicial personnel:

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

[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 for accessing the performance evaluation system;

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

[0119] Based on the deviation correlation coefficient, determining the number of associated deviation judicial personnel whose deviation correlation coefficient is less than a preset deviation correlation coefficient threshold value; when the number of associated deviation judicial personnel whose deviation correlation coefficient is less than the preset deviation correlation coefficient threshold value does not meet the requirement, determining that the target data source does not belong to the target data source for accessing the performance evaluation system;

[0120] When the number of judicial personnel with associated deviations whose deviation correlation coefficient is less than the preset deviation 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 between the evaluation items of different judicial personnel from different associated data sources, and use this as the number of overlaps in the information items;

[0122] Based on the ratio of the number of deviation matches to the number of overlapping information items, 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 the target data source for accessing the performance evaluation system.

[0123] S4 generates multiple performance evaluation plans based on the data processing order of the target data source and the associated data source connected to the performance evaluation system, determines the switching processing order of the performance evaluation plan based on the number of data sources that need to be verified and processed for the evaluation items of the personnel performance of different judicial personnel in different performance evaluation plans, and determines the evaluation processing results of different judicial personnel in combination with the recognition results of the manually input evaluation items.

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

[0125] using the evaluation items of the judicial personnel excluding manual input as verification evaluation items, and determining the order of the data sources corresponding to different verification evaluation items in the performance evaluation plan based on the data sources corresponding to the verification evaluation items;

[0126] Based on the order of the verification and evaluation items of the personnel performance of different judicial personnel in the performance evaluation plan, determine the proportion of the verification quantity of the verification and evaluation items of different judicial personnel when different data sources are processed, and based on the order of different data sources in the performance evaluation plan, determine the proportion of the verification quantity of the verification and evaluation items of judicial personnel under different numbers of verification data sources;

[0127] Based on the said order, when all the verification and evaluation items of the personnel performance of the judicial personnel are verified and processed, the number of data sources that need to be processed is determined, and it is used as the number of verification data sources for the judicial personnel. According to the number of verification data sources of different judicial personnel and the proportion of the verification number of verification evaluation items of judicial personnel under different numbers of verification data sources, the switching processing order of the performance evaluation plan is determined.

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

[0129] The performance evaluation scheme in which the number of judicial personnel is greater than the preset personnel number threshold when the number of verification data sources is less than the preset value of the number of data sources is used as an alternative evaluation scheme;

[0130] The matching evaluation scheme in the alternative evaluation scheme is determined based on the proportion of the verification number of evaluation items of judicial personnel who verify the number of data sources under the preset value of the number of data sources, and the switching processing order of the matching evaluation scheme is determined based on the average value of the proportion of the verification number of evaluation items of judicial personnel who verify the number of data sources under the preset value of the number of data sources from large to small.

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

[0132] It should be noted that when the matching evaluation scheme has a data source with a reading failure count greater than a preset failure count threshold, the matching evaluation scheme is automatically switched to the next matching evaluation scheme according to the switching processing sequence.

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

[0134] Based on the reading results of the evaluation items of the judicial personnel in different data sources and the reading results of the 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] In a second aspect, the present invention provides a computer system comprising: a memory and a processor in communication connection, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned intelligent evaluation method of judicial personnel performance based on multi-dimensional data fusion when running the computer program.

[0137] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the device, apparatus, and non-volatile computer storage medium embodiments are generally similar to the method embodiments, so their descriptions are relatively simplified. For relevant details, refer to the descriptions of the method embodiments.

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

[0139] The foregoing description is merely one or more embodiments of this specification and is not intended to limit this specification. It will be apparent to those skilled in the art that various modifications and variations may be made to one or more embodiments of this specification. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of one or more embodiments of this specification are intended to be within the scope of the claims of this specification.

Claims

1. A multi-dimensional data fusion method for intelligent evaluation of judicial personnel performance, characterized by: Specifically include: Determining evaluation items for judicial personnel based on an evaluation plan for judicial personnel's personnel performance, and determining associated data sources among the data sources based on associations between different data sources and evaluation items for different judicial personnel; Connect the associated data source to the performance evaluation system, and determine the association deviation based on the association between different associated data sources and the evaluation items of different judicial personnel. If the association deviation of judicial personnel does not meet the requirements, proceed to the next step; The data source other than the associated data source is used as the target data source, and the target data source connected to the performance evaluation system is determined based on the overlap between the target data source and the associated data source and the matching between the evaluation items of judicial personnel with different associated deviations; Based on the data processing order of the target data source and the associated data source connected to the performance evaluation system, multiple performance evaluation schemes are generated. Based on the number of data sources that need to be verified and processed for the evaluation items of the personnel performance of different judicial personnel in different performance evaluation schemes, the switching processing order of the performance evaluation schemes is determined, and combined with the recognition results of the manually input evaluation items, the evaluation processing results of different judicial personnel are determined.

2. The intelligent evaluation method for judicial personnel performance based on multi-dimensional data fusion according to claim 1 is characterized in that: The evaluation items include case closure rate, mediation rate, appeal rate, execution rate, document completion status and errors.

3. The intelligent evaluation method for judicial personnel performance based on multi-dimensional data fusion according to claim 1 is characterized in that: The method for determining the associated data source in the data source is: Determining the number of evaluation items associated with different judicial personnel for different data sources based on the association between the data sources and the evaluation items of different judicial personnel; Determining a correlation coefficient of the judicial personnel's evaluation items based on the proportion of the number of the judicial personnel's related evaluation items to the number of the judicial personnel's evaluation items; According to the correlation coefficients of the evaluation items of different judicial personnel, it is determined whether the data source is a correlated data source.

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

5. The intelligent evaluation method for judicial personnel performance based on multi-dimensional data fusion according to claim 1 is characterized in that: Determine that the related deviation of judicial personnel does not meet the requirements, including: Based on the association between different related data sources and the evaluation items of different judicial personnel, determine the judicial personnel whose evaluation items are not in the related data sources; Judicial personnel with evaluation items that are not in the associated data source are regarded as associated deviation judicial personnel; According to the proportion of the judicial personnel with correlation deviation among the judicial personnel, determine whether the correlation deviation situation of the judicial personnel with correlation deviation meets the requirements.

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

7. The intelligent evaluation method for judicial personnel performance based on multi-dimensional data fusion according to claim 1 is characterized in that: The method for determining the switching processing order of the performance evaluation scheme is as follows: using the evaluation items of the judicial personnel excluding manual input as verification evaluation items, and determining the order of the data sources corresponding to different verification evaluation items in the performance evaluation plan based on the data sources corresponding to the verification evaluation items; Based on the order of the verification and evaluation items of the personnel performance of different judicial personnel in the performance evaluation plan, determine the proportion of the verification quantity of the verification and evaluation items of different judicial personnel when different data sources are processed, and based on the order of different data sources in the performance evaluation plan, determine the proportion of the verification quantity of the verification and evaluation items of judicial personnel under different numbers of verification data sources; Based on the said order, when all the verification and evaluation items of the personnel performance of the judicial personnel are verified and processed, the number of data sources that need to be processed is determined, and it is used as the number of verification data sources for the judicial personnel. According to the number of verification data sources of different judicial personnel and the proportion of the verification number of verification evaluation items of judicial personnel under different numbers of verification data sources, the switching processing order of the performance evaluation plan is determined.

8. The intelligent evaluation method for judicial personnel performance based on multi-dimensional data fusion according to claim 7 is characterized in that: The switching processing order of the performance evaluation scheme is determined based on the number of verification data sources for different judicial personnel and the proportion of verification number of verification evaluation items for judicial personnel under different numbers of verification data sources, specifically including: The performance evaluation scheme in which the number of judicial personnel is greater than the preset personnel number threshold when the number of verification data sources is less than the preset value of the number of data sources is used as an alternative evaluation scheme; The matching evaluation scheme in the alternative evaluation scheme is determined based on the proportion of the verification number of evaluation items of judicial personnel who verify the number of data sources under the preset value of the number of data sources, and the switching processing order of the matching evaluation scheme is determined based on the average value of the proportion of the verification number of evaluation items of judicial personnel who verify the number of data sources under the preset value of the number of data sources from large to small.

9. The intelligent evaluation method for judicial personnel performance based on multi-dimensional data fusion according to claim 8, characterized in that: The matching evaluation scheme is an alternative evaluation scheme in which the average value of the verification quantity ratio of the verification evaluation items of judicial personnel who verify the number of data sources under the preset value of the number of data sources is greater than the preset verification quantity ratio threshold.

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

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