CN112381349A - Configuration method for terminal code scanning quality evaluation - Google Patents
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Abstract
The invention particularly relates to a configuration method for terminal code scanning quality evaluation. The configuration method for terminal code scanning quality evaluation comprises the steps of firstly defining the meaning of an index according to the service requirement, determining the algorithm of the index and defining the parameter of the index; then the system is configured on the index platform and distributed to the used clients from the platform; constructing a label, setting rules for indexes started in the label, and reasonably calculating the score of the indexes by adopting two modes of interval calculation and formula calculation; and finally, calculating by using a big data platform to finish the evaluation of the quality of the big code scanning. According to the configuration method for terminal code scanning quality evaluation, by means of the computing power of a big data computing platform, the development workload is greatly reduced on the basis of flexible index and label configuration, the investment cost is greatly reduced, the expandability and configurability of the system are improved, the user experience is enhanced, and the client can adjust specific parameters in combination with personalized requirements to achieve the final purpose.
Description
Technical Field
The invention relates to the technical field of large data volume index and index rule configuration, in particular to a configuration method for terminal code scanning quality evaluation.
Background
The existing code scanning quality evaluation has various modes, and the general step is to agree with the evaluation standard with a client, namely, which indexes are adopted for evaluation, and the feasibility of each index is verified according to the selected standard acquisition data. Meanwhile, in order to ensure that the evaluation client is relatively fair, the threshold value of the selected index needs to be measured and calculated, and a proper rule value (threshold value) is selected to finish the evaluation of each index. And finally, calculating an evaluation result, and performing feedback verification with the actual situation of a specific client to judge the reasonability and accuracy of code scanning quality evaluation. The whole configuration process is simple in the evaluation process, and the evaluation of a customer group with small data volume can be met.
The terminal code scanning quality evaluation modes are various and are mostly carried out based on multi-dimensional indexes, and different indexes have different calculation rules, so that the evaluation difficulty is increased. Technically, the existing quality evaluation is based on index calculation completed by a service system or a service library, or index calculation completed by establishing a single application, the group comparison related to calculation is limited, and the configured rule is not flexible. In order to realize the evaluation of a large number of customer groups, a method with flexible index selection and convenient configuration is provided by means of a large data platform.
In order to solve the evaluation difficulty and based on the complexity and diversity of code scanning quality evaluation, the invention provides a configuration method for terminal code scanning quality evaluation, aiming at simplifying index configuration, flexibly activating index rules, modularizing index calculation and diversifying index result display.
Disclosure of Invention
In order to make up for the defects of the prior art, the invention provides a simple and efficient configuration method for evaluating the code scanning quality of the terminal.
The invention is realized by the following technical scheme:
a configuration method for terminal code scanning quality evaluation is characterized by comprising the following steps:
first, index formulation
When code scanning quality evaluation is carried out, firstly, the meaning of an index is defined according to the service requirement, the algorithm of the index is determined, and the parameter of the index is defined;
second step, customer index configuration
After the indexes are established, the indexes are configured on the index platform, and the indexes are distributed to the used clients from the platform to create labels for the clients to use;
third step, label configuration
In order to complete the evaluation of the code scanning quality of the customer layer, an evaluated model is constructed, and the constructed evaluated model is called a label;
fourth step, index rule
Setting rules for indexes started in the tags, adopting two modes of interval calculation and formula calculation in order to increase calculation rules of index diversification, and selecting a calculation mode according to the requirements of customers so as to calculate the scores of the indexes;
fifth step, index and label calculation
And after the indexes and the label rules are configured, calculating by using a big data platform, and finally finishing the evaluation of the code scanning quality of the large-data-volume customer group.
In order to adapt to the variable demand, considering the universality and flexibility of the index, in the first step, the calculated dimensions are distinguished according to the meaning of the index, the calculated dimensions and the parameters related to calculation are confirmed first, and the configuration items of the index are adjusted to increase the expandability of the index.
Compared with the prior art, the method changes the specific index calculation into the configurable index calculation, namely, the flexibility of the index is increased through the fixation of the index algorithm, the selection of the dimension and the configurability of the parameter, and the application range and the multiplexing width of the index are greatly improved.
In the second step, the universality of the indexes is checked after the indexes are established, and if the universality is strong, the indexes are added into a platform index library for standby use;
the indexes added into the platform index library are universal and configurable, and when other clients use the same indexes, the indexes are directly configured from the platform, so that the workload of repeated development is avoided.
In the third step, the labels are composed of different indexes, the emphasis point of each index in different labels or different periods of the same label is different due to different work emphasis points of the client, in order to distinguish the emphasis point (priority level) of each index, a weight is introduced in the process of model configuration, and each index in the labels can distinguish the priority level according to the weight value, so that the label value of all clients is calculated.
The weighting value is that indexes in the label are subjected to a percentile system, each index gives a fixed weight, the actual score of each index is calculated firstly, the weight score of each index on the label layer is calculated according to the weight of the index, and finally all the index weight scores are added to determine the label score of the client, so that the client score is calculated.
In the label model, a client starts different indexes as required to calculate the label, and can flexibly adjust to increase the evaluation range and accuracy.
And in the fourth step, the interval is calculated into data sections which are distinguished according to specific indexes, each data section corresponds to a corresponding score, and when the indexes fall within a certain range, the scores of the interval in which the indexes are located are the index scores.
And in the fourth step, the formula calculation adopts the formula form to complete the description of the index rule and directly calculate the index score.
Compared with formula calculation, interval calculation is simple in arrangement, and the complexity of interval calculation lies in that the selection of the interval limit value needs to be combined with the actual situation and a large amount of data to calculate the rule limit value, and then the setting of the index rule is completed.
The difficulty of the formula calculation is the regular realization of the index score in the calculation, and because the large data platform is adopted for unified calculation, the whole configuration is required to be carried out to increase the flexibility of the configuration.
The invention has the beneficial effects that: according to the configuration method for terminal code scanning quality evaluation, by means of the computing power of a big data computing platform, the development workload is greatly reduced on the basis of flexible index and label configuration, the investment cost is greatly reduced, the expandability and configurability of the system are improved, the user experience is enhanced, and the client can adjust specific parameters in combination with personalized requirements to achieve the final purpose.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the embodiment of the present invention. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The configuration method for terminal code scanning quality evaluation comprises the following steps:
first, index formulation
When code scanning quality evaluation is carried out, firstly, the meaning of an index is defined according to the service requirement, the algorithm of the index is determined, and the parameter of the index is defined;
second step, customer index configuration
After the indexes are established, the indexes are configured on the index platform, and the indexes are distributed to the used clients from the platform to create labels for the clients to use;
third step, label configuration
In order to complete the evaluation of the code scanning quality of the customer layer, an evaluated model is constructed, and the constructed evaluated model is called a label;
fourth step, index rule
Setting rules for indexes started in the tags, adopting two modes of interval calculation and formula calculation in order to increase calculation rules of index diversification, and selecting a calculation mode according to the requirements of customers so as to calculate the scores of the indexes;
fifth step, index and label calculation
And after the indexes and the label rules are configured, calculating by using a big data platform, and finally finishing the evaluation of the code scanning quality of the large-data-volume customer group.
In order to adapt to the variable demand, considering the universality and flexibility of the index, in the first step, the calculated dimensions are distinguished according to the meaning of the index, the calculated dimensions and the parameters related to calculation are confirmed first, and the configuration items of the index are adjusted to increase the expandability of the index.
Compared with the prior art, the method changes the specific index calculation into the configurable index calculation, namely, the flexibility of the index is increased through the fixation of the index algorithm, the selection of the dimension and the configurability of the parameter, and the application range and the multiplexing width of the index are greatly improved.
In the second step, the universality of the indexes is checked after the indexes are established, and if the universality is strong, the indexes are added into a platform index library for standby use;
the indexes added into the platform index library are universal and configurable, and when other clients use the same indexes, the indexes are directly configured from the platform, so that the workload of repeated development is avoided.
In the third step, the labels are composed of different indexes, the emphasis point of each index in different labels or different periods of the same label is different due to different work emphasis points of the client, in order to distinguish the emphasis point (priority level) of each index, a weight is introduced in the process of model configuration, and each index in the labels can distinguish the priority level according to the weight value, so that the label value of all clients is calculated.
The weighting value is that indexes in the label are subjected to a percentile system, each index gives a fixed weight, the actual score of each index is calculated firstly, the weight score of each index on the label layer is calculated according to the weight of the index, and finally all the index weight scores are added to determine the label score of the client, so that the client score is calculated.
In the label model, a client starts different indexes as required to calculate the label, and can flexibly adjust to increase the evaluation range and accuracy.
And in the fourth step, the interval is calculated into data sections which are distinguished according to specific indexes, each data section corresponds to a corresponding score, and when the indexes fall within a certain range, the scores of the interval in which the indexes are located are the index scores.
And in the fourth step, the formula calculation adopts the formula form to complete the description of the index rule and directly calculate the index score.
Compared with formula calculation, interval calculation is simple in arrangement, and the complexity of interval calculation lies in that the selection of the interval limit value needs to be combined with the requirement condition of the interval and a large amount of data to calculate the rule limit value, and then the setting of the index rule is completed.
The difficulty of the formula calculation is the regular realization of the index score in the calculation, and because the large data platform is adopted for unified calculation, the whole configuration is required to be carried out to increase the flexibility of the configuration.
Fifth step, index and label calculation
And after the indexes and the label rules are configured, calculating by using a big data platform, and finally finishing the evaluation of the code scanning quality of a large number of customer groups.
The above-described embodiment is only one specific embodiment of the present invention, and general changes and substitutions by those skilled in the art within the technical scope of the present invention are included in the protection scope of the present invention.
Claims (8)
1. A configuration method for terminal code scanning quality evaluation is characterized by comprising the following steps:
first, index formulation
When code scanning quality evaluation is carried out, firstly, the meaning of an index is defined according to the service requirement, the algorithm of the index is determined, and the parameter of the index is defined;
second step, customer index configuration
After the indexes are established, the indexes are configured on the index platform, and the indexes are distributed to the used clients from the platform to create labels for the clients to use;
third step, label configuration
In order to complete the evaluation of the code scanning quality of the customer layer, an evaluated model is constructed, and the constructed evaluated model is called a label;
fourth step, index rule
Setting rules for indexes started in the tags, adopting two modes of interval calculation and formula calculation in order to increase calculation rules of index diversification, and selecting a calculation mode according to the requirements of customers so as to calculate the scores of the indexes;
fifth step, index and label calculation
And after the indexes and the label rules are configured, calculating by using a big data platform, and finally finishing the evaluation of the code scanning quality of the large-data-volume customer group.
2. The configuration method for terminal code scanning quality evaluation according to claim 1, characterized in that: in the first step, the calculation dimensionality is distinguished according to the meaning of the index, the calculation dimensionality of the index and the parameters related to calculation are confirmed first, and the configuration items of the index are adjusted to increase the expandability of the index.
3. The configuration method for terminal code scanning quality evaluation according to claim 1, characterized in that: in the second step, the universality of the indexes is checked after the indexes are established, and if the universality is strong, the indexes are added into a platform index library for standby use;
the indexes added into the platform index library are universal and configurable, and when other clients use the same indexes, the indexes are directly configured from the platform, so that the workload of repeated development is avoided.
4. The configuration method for terminal code scanning quality evaluation according to claim 1, characterized in that: in the third step, the labels are composed of different indexes, the emphasis point of each index in different labels or different periods of the same label is different due to different work emphasis points of the client, in order to distinguish the emphasis point of each index, a weight is introduced in the process of model configuration, and each index in the labels can be prioritized according to the weight value, so that the overall label value of all the clients is calculated.
5. The configuration method for terminal code scanning quality evaluation according to claim 4, wherein: the weighting value is that indexes in the label are subjected to a percentile system, each index gives a fixed weight, the actual score of each index is calculated firstly, the weight score of each index on the label layer is calculated according to the weight of the index, and finally all the index weight scores are added to determine the label score of the client, so that the client score is calculated.
6. The configuration method for terminal code scanning quality evaluation according to claim 5, wherein: in the label model, a client starts different indexes as required to calculate the label, and can flexibly adjust to increase the evaluation range and accuracy.
7. The configuration method for terminal code scanning quality evaluation according to claim 1, characterized in that: and in the fourth step, the interval is calculated into data sections which are distinguished according to specific indexes, each data section corresponds to a corresponding score, and when the indexes fall within a certain range, the scores of the interval in which the indexes are located are the index scores.
8. The configuration method for terminal code scanning quality evaluation according to claim 1, characterized in that: and in the fourth step, the formula calculation adopts the formula form to complete the description of the index rule and directly calculate the index score.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105574653A (en) * | 2015-12-14 | 2016-05-11 | 四川长虹电器股份有限公司 | Supplier evaluation and selection method based on data warehouse |
| CN107123011A (en) * | 2016-08-26 | 2017-09-01 | 北京小度信息科技有限公司 | Trade company recommends method, sets up the method and relevant apparatus of trade company's evaluation model |
| US20200019913A1 (en) * | 2017-03-28 | 2020-01-16 | Huawei Technologies Co., Ltd. | Service Quality Evaluation Method and Terminal Device |
| CN111401778A (en) * | 2020-03-31 | 2020-07-10 | 天津市商务局(天津市人民政府口岸服务办公室) | Port enterprise evaluation method and device and storage medium |
| CN111652480A (en) * | 2020-05-20 | 2020-09-11 | 贯航信息技术南京有限公司 | Business evaluation management method based on enterprise application |
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- 2020-10-14 CN CN202011094382.0A patent/CN112381349A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105574653A (en) * | 2015-12-14 | 2016-05-11 | 四川长虹电器股份有限公司 | Supplier evaluation and selection method based on data warehouse |
| CN107123011A (en) * | 2016-08-26 | 2017-09-01 | 北京小度信息科技有限公司 | Trade company recommends method, sets up the method and relevant apparatus of trade company's evaluation model |
| US20200019913A1 (en) * | 2017-03-28 | 2020-01-16 | Huawei Technologies Co., Ltd. | Service Quality Evaluation Method and Terminal Device |
| CN111401778A (en) * | 2020-03-31 | 2020-07-10 | 天津市商务局(天津市人民政府口岸服务办公室) | Port enterprise evaluation method and device and storage medium |
| CN111652480A (en) * | 2020-05-20 | 2020-09-11 | 贯航信息技术南京有限公司 | Business evaluation management method based on enterprise application |
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