A multi-level evaluation index representation, calculation and storage technology

Abstract

The application discloses a kind of multilevel evaluation index representation, calculation and storage technology, including external business detail storage, also including index definition module, index definition storage, index calculation module, index result storage, index result query module;The application divides index into basic statistical index, basic qualitative index, comprehensive statistical index, comprehensive evaluation index, and specifically defines the dependence and generation relationship of these indexes.Then based on scene induction, several commonly used calculation rule models are summarized, and the whole process does not expose more attack surface, and the security, practicality and scalability are considered.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of index evaluation, in particular to a multi-level evaluation index representation, calculation and storage technology. BACKGROUND

[0002] The system related to comprehensive evaluation, such as the evaluation system and the situation awareness system, often needs to build a complete index system for evaluation based on the business, so as to facilitate the user to quickly build the overall understanding of the business based on it. The whole process of building the index system includes business design, system implementation and continuous optimization of the index system. The existing process includes the following schemes.

[0003] Scheme 1: Specific business scheme. Many systems and patents belong to this scheme. The focus of this scheme is not to build an independent and universal index management system, but to describe the various data processing technologies or steps involved in the process of building a certain index system in a specific business field or scene, which is a summary of specific business and technology selection.

[0004] Scheme 2: Index definition and implementation separation scheme. Some patents and business systems also involve this scheme. This scheme proposes to build an index management system to realize the addition, deletion, modification and query of index definition. Some patents further propose to associate the index definition and the index calculation result, so as to realize the synchronous query of the index calculation result.

[0005] Scheme 1 is suitable for business scenarios that have summarized a set of fixed data processing processes, and is difficult to be universal after the scene changes. Scheme 2 can quickly complete the initial project delivery, but it is difficult to maintain the addition, deletion and modification of indexes in the later operation process, and it is difficult to continuously ensure the consistency of index definition and implementation. SUMMARY

[0006] The technical problem to be solved by the present application is the defects of the background art. The present application provides a multi-level evaluation index representation, calculation and storage technology. Several commonly used calculation rule models are summarized based on the scene, and the whole process does not expose more attack surface, which balances the security, practicality and scalability.

[0007] The present application adopts the following technical solutions to solve the above technical problems:

[0008] A multi-level evaluation index representation, calculation and storage technology, comprising an external business detail storage 11, further comprising an index definition module 13, an index definition storage 12, an index calculation module 14, an index result storage 16, and an index result query module 15.

[0009] The external business detail storage 11 is prepared by a business system, and stores multiple detail tables to be counted in a relational database; the index definition module 13 is used for defining business indexes for users, including basic statistical indexes, basic qualitative indexes, comprehensive statistical indexes, and comprehensive evaluation indexes; the definition of an index includes an index name, an index type, an index business meaning, a qualitative standard, other indexes relied on, and a generation rule, and the definition of the index is stored in the index definition storage 12;

[0010] The index calculation module 14 is triggered by a user or a scheduler to perform specific index calculation operations; wherein the basic indexes are calculated based on the detail data in the external business detail storage 11 and the generation rule data in the index definition storage 12, and the calculation results are stored in the index result storage 16; the comprehensive indexes are calculated based on the definition and calculation results of other indexes relied on and the definition parameters of the comprehensive indexes, and the calculation results are also stored in the index result storage 16;

[0011] The index result query module 15 is used to provide index definition query and index calculation result query functions for upper-layer applications.

[0012] Preferably, the method comprises the following steps:

[0013] Step 1, defining and calculating the dependent basic statistical indexes; the basic statistical index definition stage needs to specify an index name, an index type-basic statistical index, an index business meaning, an index data source, an index generation rule, and a qualitative rule; the basic index calculation stage calculates the statistical results based on the data source and the generation rule specified in the definition, and stores the statistical results into the index result storage 16; after the calculation is completed, the index result query module 15 is used to check and verify whether the generation rule in the definition stage can generate the expected calculation results, and if there is a deviation, the generation rule in the definition is adjusted to recalculate until all the basic statistical indexes are constructed and meet the expectations;

[0014] Step 2, defining and calculating the dependent basic qualitative indexes; the basic qualitative index definition stage needs to specify an index name, an index type-basic qualitative index, an index business meaning, an index data source, an index generation rule, and a qualitative rule; the subsequent calculation, verification, and optimization processes are the same as step 1;

[0015] Step 3, defining and calculating the dependent comprehensive statistical indexes; the comprehensive statistical index definition stage needs to specify an index name, an index type-comprehensive statistical index, an index business meaning, other indexes relied on, an index generation rule, and a qualitative rule; the subsequent calculation, verification, and optimization processes are the same as step 1.

[0016] Step 4, define dependent comprehensive evaluation indexes and calculate. The comprehensive evaluation index definition stage needs to specify the index name, index type-comprehensive evaluation index, index business meaning, other indexes it depends on, index generation rule, qualitative rule; in addition to storage definition, it also needs to judge whether there is a circular dependency of the index to avoid deadlock; the calculation stage of the comprehensive evaluation index is based on the calculation results of its dependent indexes and the generation rule of the index, and a specific calculation model is selected for calculation; the user can define which indexes or which dimensions within the indexes participate in weighting and support modification of the weighting coefficient; after modification, one-key recalculation is performed until all dependent comprehensive evaluation indexes are calculated and meet the expectation;

[0017] Step 5, define the final comprehensive evaluation index and calculate. The definition, calculation, verification and optimization process is the same as step 4; after this step is completed, the definition and calculation of the entire multi-level evaluation index are completed, and the index definition and calculation results can be displayed and applied through the index result query module 15.

[0018] Compared with the prior art, the beneficial effects of the present application are:

[0019] 1. The multi-level evaluation index representation, calculation and storage technology provided by the present application decouples the construction process of the index system from the specific business data, can quickly construct the index system required by the business system based thereon and support continuous optimization, and saves development and operation costs.

[0020] 2. The multi-level evaluation index representation, calculation and storage technology provided by the present application can add or modify comprehensive indexes and basic indexes according to business needs, can trigger calculation and apply the results to the existing evaluation system with one key, realizes the rapid construction and continuous optimization of indexes.

[0021] 3. The multi-level evaluation index representation, calculation and storage technology provided by the present application divides the indexes into basic statistical indexes, basic qualitative indexes, comprehensive statistical indexes and comprehensive evaluation indexes, and specifically defines the dependency and generation relationship of these indexes. Then several commonly used calculation rule models are summarized based on the scene, and the entire process does not expose more attack surface, and the security, practicality and scalability are considered. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the specific embodiments or prior art of the present application, the drawings needed in the specific embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings based on these drawings without creative labor.

[0023] Figure 1A schematic diagram of a multi-level evaluation index representation, calculation and storage technology composition;

[0024] Figure 2 A multi-level evaluation index construction flow chart. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0026] Referring to Figure 1 The present application discloses a multi-level evaluation index representation, calculation and storage technology. The system can be used as a core functional component of a situation awareness system to quickly realize an index system in business design. The system depends on an external business detail storage 11. The composition of the system includes an index definition module 13, an index definition storage 12, an index calculation module 14, an index result storage 16 and an index result query module 15.

[0027] The external dependence-external business detail storage 11 is prepared and generated by a business system. Generally, it is a plurality of detail tables stored in a relational database to be counted. The index definition module 13 is used to define business indexes for users, including basic statistical indexes, basic qualitative indexes, comprehensive statistical indexes and comprehensive evaluation indexes. The definition of the indexes includes an index name, an index type, an index business meaning, a qualitative standard, other dependent indexes, a generation rule and the like. These information is finally stored in the index definition storage 12. It needs to be declared that the generation rule of part of the basic indexes is relatively complex. Based on security and cost considerations, such generation rule does not support user creation, but is built-in in the system, and only supports user to view and modify part of the key parameters.

[0028] The index calculation module 14 is triggered by a user or a scheduler to perform specific index calculation operations. The basic indexes are calculated based on the detail data in the external business detail storage 11 and the generation rule data in the index definition storage 12. The calculation results are stored in the index result storage 16. The comprehensive indexes are calculated based on the definition and calculation results of the other dependent indexes and the definition parameters of the comprehensive indexes. The calculation results are also stored in the index result storage 16.

[0029] The index result query module 15 is used to face the upper layer application to provide index definition query and index calculation result query functions.

[0030] Referring to Figure 2 The following will be described in combination with Figure 2Introduce a kind of multi-level comprehensive evaluation index representation, calculation and storage method, including the following steps:

[0031] Step 1, define the dependent basic statistical indicators and calculate. The basic statistical indicator definition stage needs to specify the indicator name (such as the number of students in each class), the indicator type-basic statistical indicator, the indicator business meaning, the indicator data source (such as the student detail table in the external business detail table), the indicator generation rule (including statistical dimensions such as class, calculation subscripts such as count, filtering conditions such as first grade), qualitative rules (optional, such as class size less than 10 people is small-scale class, 11-30 people is medium-scale class, and class size more than 30 is large-scale class). The basic indicator calculation stage is based on the data source and generation rule specified in the definition to calculate the statistical result and store it in the indicator result storage 16. After calculation, the generation rule in the definition stage can be checked and verified through the indicator result query module 15 to see if it can generate the expected calculation result, if there is deviation, the generation rule in the definition can be adjusted and recalculated, until all the basic statistical indicators are constructed and meet the expectations.

[0032] Step 2, define the dependent basic qualitative indicators and calculate. The basic qualitative indicator definition stage needs to specify the indicator name (such as whether all students in the class have passed the English level four), the indicator type-basic qualitative indicator, the indicator business meaning, the indicator data source (such as the student English level four test score table in the external business detail table), the indicator generation rule (including statistical dimensions such as class, calculation subscripts such as self-defined operator, filtering conditions such as second grade boys), and qualitative rules (mandatory, 1 if true, 0 otherwise). The subsequent calculation, verification and optimization process is the same as step 1.

[0033] Step 3, define the dependent comprehensive statistical indicators and calculate. The comprehensive statistical indicator definition stage needs to specify the indicator name (such as the proportion of English level four passing in the class), the indicator type-comprehensive statistical indicator, the indicator business meaning, its dependent basic indicators (such as the number of English level four passing in the class and the total number of students in the class), the indicator generation rule (including statistical dimensions such as class, calculation rule for dependent indicators 1 / dependent indicators 2, filtering conditions such as third grade), and qualitative rules (optional, such as less than 50% passing rate for poor class, 50%-80% for ordinary class, and more than 80% for excellent class). The subsequent calculation, verification and optimization process is the same as step 1.

[0034] Step 4, define the dependent comprehensive evaluation index and calculate. The comprehensive evaluation index definition stage needs to specify the index name (such as class learning situation comprehensive score), index type-comprehensive evaluation index, index business meaning, its dependent other indexes (such as class English test average score, class Chinese test average score, class mathematics test average score, class other subject award score), index generation rule (including statistical dimension such as class, calculation model such as simple weighted model, specific model parameter is English average score*0.2+Chinese average score*0.3+mathematics average score*0.3+other subject award score*0.2, screening condition such as fourth grade), qualitative rule (optional item, such as class learning situation comprehensive score score within 60 is poor, 60-79 is medium, 80-89 is good, 90-100 is excellent). In addition, when storing the definition, it is also necessary to judge whether there is a circular dependency of the index to avoid deadlock. The calculation stage of the comprehensive evaluation index is based on the calculation results of its dependent indexes and the generation rule of the index, and a specific calculation model (such as a simple weighted model, a classification weighted model according to the associated index dimension, an index qualitative scoring model, etc.) is selected for calculation. The user can define which indexes or which dimensions within which indexes participate in weighting and support modifying the weighting coefficient. After modification, one-key recalculation is performed until all dependent comprehensive evaluation indexes are calculated and meet the expectation.

[0035] Step 5, define the final comprehensive evaluation index and calculate. The definition, calculation, verification and optimization process is the same as step 4. After this step is completed, the definition and calculation of the entire multi-level evaluation index are completed, and subsequent index result query module 15 can be used to display and apply the index definition and calculation results.

[0036] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement to part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for representing, calculating, and storing multi-level evaluation indicators, characterized in that, It includes external business details storage (11), indicator definition module (13), indicator definition storage (12), indicator calculation module (14), indicator result storage (16), and indicator result query module (15); The external business detail storage (11) is prepared and generated by the business system and stored in multiple detail tables to be statistically analyzed in the relational database; The indicator definition module (13) is used to define business indicators for users, including basic statistical indicators, basic qualitative indicators, comprehensive statistical indicators, and comprehensive evaluation indicators. The definition of an indicator includes the indicator name, indicator type, indicator business meaning, qualitative standard, other dependent indicators, and generation rules. The definition of an indicator is stored in the indicator definition storage (12). The indicator calculation module (14) is triggered by the user or scheduler to perform specific indicator calculation operations; the basic indicators are calculated based on the detailed data in the external business detail storage (11) and the generation rule data in the indicator definition storage (12), and the calculation results are stored in the indicator result storage (16). The comprehensive index is calculated based on the definition and calculation results of other indicators it depends on and the definition parameters of the comprehensive index itself. The calculation results are also stored in the index result storage (16). The indicator result query module (15) is used to provide query functions for indicator definitions and indicator calculation results for upper-layer applications; Includes the following steps: Step 1: Define and calculate the basic statistical indicators that are relied upon; In the basic statistical indicator definition stage, it is necessary to specify the indicator name, indicator type - basic statistical indicator, indicator business meaning, indicator data source, indicator generation rules, and qualitative rules; In the basic indicator calculation stage, the statistical results are calculated based on the data source and generation rules specified in the definition and stored in the indicator result storage (16); After the calculation is completed, check and verify whether the generation rules in the definition stage can generate the expected calculation results through the indicator result query module (15). If there is a deviation, adjust the generation rules in the definition and recalculate with one click until all basic statistical indicators are constructed and meet expectations. Step 2: Define and calculate the basic qualitative indicators that are dependent on the indicator; the basic qualitative indicator definition stage requires specifying the indicator name, indicator type - basic qualitative indicator, indicator business meaning, indicator data source, indicator generation rules, and qualitative rules; the subsequent calculation, verification, and optimization process is the same as in Step 1; Step 3: Define and calculate the dependent comprehensive statistical indicators; the comprehensive statistical indicator definition stage requires specifying the indicator name, indicator type - comprehensive statistical indicator, indicator business meaning, its dependent basic indicators, indicator generation rules, and qualitative rules; the subsequent calculation, verification, and optimization processes are the same as in Step 1; Step 4: Define and calculate the dependent comprehensive evaluation indicators; the definition stage of the comprehensive evaluation indicator requires specifying the indicator name, indicator type - comprehensive evaluation indicator, indicator business meaning, other indicators it depends on, indicator generation rules, and qualitative rules; in addition, when storing the definition, it is also necessary to check whether there are circular dependencies of indicators to avoid deadlock; the calculation stage of the comprehensive evaluation indicator is based on the calculation results of its dependent indicators and the generation rules of this indicator, and selects a specific calculation model for calculation; users can define which indicators or which dimensions within which indicators participate in the weighting and support modifying the weighting coefficients; After modification, recalculate with one click until all dependent comprehensive evaluation indicators are calculated and meet expectations; Step 5: Define and calculate the final comprehensive evaluation index; the definition, calculation, verification, and optimization process is the same as in Step 4. After this step is completed, the definition and calculation of the entire multi-level evaluation index are finished. The index definition and calculation results can be displayed and applied through the index result query module (15).

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