CN111277451B - Service evaluation method, device, terminal equipment and medium - Google Patents
Service evaluation method, device, terminal equipment and medium Download PDFInfo
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- CN111277451B CN111277451B CN201811481335.4A CN201811481335A CN111277451B CN 111277451 B CN111277451 B CN 111277451B CN 201811481335 A CN201811481335 A CN 201811481335A CN 111277451 B CN111277451 B CN 111277451B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/06—Generation of reports
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/04—Processing captured monitoring data, e.g. for logfile generation
Abstract
The application discloses a service evaluation method, a device, terminal equipment and a medium, which belong to the technical field of communication, wherein the method comprises the steps of obtaining monitoring data of user network access, wherein the monitoring data comprises index values of each network access; respectively counting the access times corresponding to each index value according to each index value contained in the monitoring data, and respectively determining the access probability corresponding to each index value according to the access times corresponding to each index value; determining a first sum of access probabilities corresponding to index values larger than a preset index threshold value and a second sum of access probabilities corresponding to index values not larger than the preset index threshold value; and obtaining a service evaluation result according to the ratio of the first sum to the second sum. Therefore, the probability distribution area corresponding to each index value is divided according to the preset index threshold, and the service evaluation result is obtained according to each divided access probability, so that the accuracy of the service evaluation result of the user is improved.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method, an apparatus, a terminal device, and a medium for service evaluation.
Background
With the development of internet technology, the number of internet users and the amount of access are increasing. In order to further improve the service quality of internet access and optimize internet services, service evaluation on the service quality of internet services is generally required.
In the prior art, when service quality of internet service is evaluated, the following methods are generally adopted:
the first mode is as follows: monitoring the network access state of each user in a set time period (such as within one month), acquiring each index value of a single service index, and determining a service evaluation result according to the average value of each index value. The service index is used for evaluating the service quality of the internet service.
For example, if the service index is access delay, the user perception is better when the average access delay value is 3s than when the average access delay value is 5 s; assuming that the service index is the downloading rate, the user perception is better when the downloading average rate is 2 Mbps than when the downloading average rate is 1 Mbps.
The second way is: monitoring the network access state of each user in a set time period (e.g., within one month), respectively determining the index average value of each service index, and determining a comprehensive service evaluation result according to the index average value of each service index.
However, the average value of the index values is easily affected by the extreme value image, and if the data has a bipolar differentiation phenomenon or has a prominent abnormal value, the obtained service evaluation result is inaccurate, and cannot reflect the change of the actual index value, and cannot reflect the real network quality.
Disclosure of Invention
The embodiment of the application provides a service evaluation method, a service evaluation device, terminal equipment and a medium, which are used for improving the accuracy of a service evaluation result when the service quality of internet service is evaluated.
In one aspect, a method for service evaluation is provided, including:
acquiring monitoring data of user network access, wherein the monitoring data comprises index values of each network access;
respectively counting the access times corresponding to each index value according to each index value contained in the monitoring data, and respectively determining the access probability corresponding to each index value according to the access times corresponding to each index value;
determining a first sum of access probabilities corresponding to index values larger than a preset index threshold value and a second sum of access probabilities corresponding to index values not larger than the preset index threshold value;
and obtaining a service evaluation result according to the ratio of the first sum to the second sum.
Preferably, after the access probability corresponding to each index value is determined, before determining the first sum of the access probabilities corresponding to the index values greater than the preset threshold, the method includes:
screening the index values according to the access probability corresponding to the index values to obtain a screening set;
and respectively determining the new access probability of each index value in the screening set according to the access times of the index values in the screening set.
Preferably, the screening the index values according to the access probability corresponding to each index value to obtain a screening set includes:
sequencing the corresponding index values according to the sequence of the access probability from high to low;
setting the initial cumulative probability to be 0, and respectively executing the following steps aiming at each index value according to the sequence until the obtained cumulative probability is higher than a preset threshold value: and determining the sum of the access probability corresponding to one index value and the current cumulative probability as a new cumulative probability, and adding the index value into the set screening set.
Preferably, further comprising:
screening out network elements corresponding to index values which are not greater than a preset index threshold value according to the incidence relation between each network element and the index value which is also contained in the monitoring data;
respectively aiming at each screened network element, executing the following steps: determining the quality difference rate of a network element according to the access times of all index values of the network element, which are not more than a preset index threshold, and the total access times corresponding to the network element;
and determining the quality difference network elements according to the quality difference rate of each network element.
In one aspect, a service evaluation apparatus is provided, including:
the acquisition unit is used for acquiring monitoring data of user network access, and the monitoring data comprises index values of each network access;
a counting unit, configured to count access times corresponding to each index value according to each index value included in the monitoring data, and determine an access probability corresponding to each index value according to the access times corresponding to each index value;
the determining unit is used for determining a first sum of the access probabilities corresponding to the index values which are greater than the preset index threshold value and a second sum of the access probabilities corresponding to the index values which are not greater than the preset index threshold value;
and the obtaining unit is used for obtaining a service evaluation result according to the ratio of the first sum to the second sum.
Preferably, the statistical unit is further configured to:
screening the index values according to the access probability corresponding to the index values to obtain a screening set;
and respectively determining the new access probability of each index value in the screening set according to the access times of the index values in the screening set.
Preferably, the statistical unit is further configured to: sequencing the corresponding index values according to the sequence of the access probability from high to low;
setting the initial cumulative probability to be 0, and respectively executing the following steps aiming at each index value according to the sequence until the obtained cumulative probability is higher than a preset threshold value: and determining the sum of the access probability corresponding to one index value and the current cumulative probability as a new cumulative probability, and adding the index value into the set screening set.
Preferably, the obtaining unit is further configured to:
screening out network elements corresponding to index values which are not greater than a preset index threshold value according to the incidence relation between each network element and the index value which is also contained in the monitoring data;
respectively aiming at each screened network element, executing the following steps: determining the quality difference rate of a network element according to the access times of all index values of the network element, which are not more than a preset index threshold, and the total access times corresponding to the network element;
and determining the quality difference network elements according to the quality difference rate of each network element.
In one aspect, a terminal device is provided, which includes at least one processing unit and at least one storage unit, where the storage unit stores a computer program, and when the program is executed by the processing unit, the processing unit is caused to execute the steps of any one of the service evaluation methods described above.
In one aspect, a computer-readable medium is provided, which stores a computer program executable by a terminal device, and when the program is run on the terminal device, causes the terminal device to perform the steps of any of the above-mentioned service evaluation methods.
In the service evaluation method, the service evaluation device, the terminal device and the medium provided by the embodiment of the application, monitoring data of user network access is obtained, and the monitoring data comprises index values of each network access; respectively counting the access times corresponding to each index value according to each index value contained in the monitoring data, and respectively determining the access probability corresponding to each index value according to the access times corresponding to each index value; determining a first sum of access probabilities corresponding to index values larger than a preset index threshold value and a second sum of access probabilities corresponding to index values not larger than the preset index threshold value; and obtaining a service evaluation result according to the ratio of the first sum to the second sum. Therefore, the probability distribution area corresponding to each index value is divided according to the preset index threshold, and the service evaluation result is obtained according to each divided access probability, so that the accuracy of the service evaluation result of the user is improved.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a flowchart of an implementation of a service evaluation method in an embodiment of the present application;
FIG. 2a is a diagram illustrating an example of a probability distribution according to an embodiment of the present application;
FIG. 2b is a schematic diagram of a probability distribution ranking according to an embodiment of the present application;
FIG. 2c is a diagram illustrating an example of an effective probability distribution according to an embodiment of the present application;
FIG. 2d is an exemplary diagram of a probability distribution area partition in an embodiment of the present application;
fig. 2e is a diagram illustrating a service evaluation example in an embodiment of the present application;
FIG. 2f is a diagram illustrating an example of a quality-poor IP in an embodiment of the present application;
fig. 3 is a schematic structural diagram of a service evaluation apparatus in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more clearly apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In order to improve the accuracy of a service evaluation result of a user when evaluating the network access quality of the user, embodiments of the present application provide a service evaluation method, apparatus, terminal device, and medium.
Referring to fig. 1, a flowchart of an implementation of a service evaluation method provided in the present application is shown. The specific implementation flow of the method is as follows:
step 100: and the server acquires monitoring data during network access of the user within a set time period.
Optionally, the set time period may be set according to actual needs, and may be 1 month, one year, 1 day, and the like. The monitoring data is obtained by monitoring the network state of the network access of each user. The monitoring data may be stored in the form of access records, one access record comprising: the network element may be a source Internet Protocol (IP) for network access, a core network element, a domain name, a Uniform Resource Locator (URL), an IP for home service, and identification information of the user terminal.
Optionally, the service index may be one or more.
For example, the service index may be access delay, download rate, and the like.
For example, one access record contained in the monitoring data is: home service address IP is 221.136.23.34, URL: https:// basic. so. com/doc, access latency: 3s in the sequence.
Step 101: and the server counts the access times corresponding to each index value of the specified service index according to the monitoring data.
Specifically, the server groups each access record included in the monitoring data according to an index value of a specified service index, and counts the number of access records in each group, that is, the number of accesses. That is, the number of accesses corresponding to each index value is counted.
For example, if the access time delays of 3 access records in the monitoring data are all 5s, the access times corresponding to the statistical access time delay of 5s are 3.
Step 102: and the server respectively determines the access probability corresponding to each index value according to the access times corresponding to the index values.
Specifically, the server determines the total number of access times according to the number of access times corresponding to each index value, and determines the access probability corresponding to each index value according to the ratio of the number of access times of each index value to the total number of access times.
Fig. 2a shows an exemplary graph of a probability distribution. The horizontal axis represents index values, and the vertical axis represents access probabilities.
Optionally, when determining the access probability corresponding to an index value, the following formula may be adopted:
where f (x) is the access probability corresponding to the index value x, x is the index value, y is the number of accesses, i is the index value number, and n is the total number of index values.
Thus, the probability distribution of the access probability corresponding to each index value can be determined.
Step 103: and the server screens the index values according to the access probability corresponding to the index values to obtain a screening set.
Specifically, in S301, the server sorts the index values in the order of the highest access probability to the lowest access probability.
Fig. 2b is a schematic diagram of probability distribution sorting. The horizontal axis represents index values, and the vertical axis represents access probabilities. MODE (x)1、MODE(x)2、MODE(x)3… … are index values, and are sorted in the order of the corresponding access probabilities from high to low.
S302, the server sets the initial cumulative probability to be 0, and according to the sequence, the following steps are executed respectively for each index value:
and determining the sum of the access probability corresponding to the index value and the current cumulative probability, determining the sum as a new cumulative probability, and if the new cumulative probability is higher than a preset threshold value, ending the process.
For example, assuming that the preset threshold is 0.8, the server sequentially accumulates the access probabilities corresponding to the index values according to the sequence of the access probabilities until the obtained accumulated probability is higher than 0.8.
S303, screening each index value subjected to probability accumulation by the server to obtain a screening set.
In the embodiment of the present application, only the determination of the screening set according to the access probability is taken as an example for explanation, and in practical application, each index value may be screened according to the number of accesses and the like to obtain the screening set.
Therefore, access noise can be removed in a screening mode, effective data can be screened, and the influence of abnormal values on an evaluation result can be removed, so that the subsequently obtained service evaluation result is close to the perception of most users, and the service quality is truly reflected.
Step 104: and the server respectively determines the new access probability of each index value in the screening set according to the access times of each index value in the screening set.
Specifically, the server determines the total access times of the selected index values according to the access times of the selected index values, and determines corresponding new access probabilities according to the ratio of the access times of each selected index value to the total access times of the selected index values.
For example, referring to FIG. 2c, an exemplary graph of an effective probability distribution is shown. The horizontal axis represents index value x, and the vertical axis represents access probability f (x). FIG. 2c shows the distribution of new access probabilities for each metric value in the filter set.
Step 105: and the server obtains a service evaluation result according to the access probability of each index value.
Specifically, in step S501, the server obtains a preset index threshold. The preset index threshold is an index threshold set by means of expert experience and the like.
S502, the server determines a first sum of the access probabilities corresponding to the index values larger than a preset index threshold value and a second sum of the access probabilities corresponding to the index values not larger than the preset index threshold value.
S503, the server determines the ratio of the first sum to the second sum as a goodness ratio, and determines a service evaluation result according to the goodness ratio.
FIG. 2d is a diagram illustrating an exemplary division of probability distribution areas. The server divides the probability distribution area into x according to a preset index threshold valuek-xnA region of high quality in between, and xm-xkThe area of quality difference therebetween.
Optionally, when determining the quality ratio, the following formula may be adopted:
wherein, δ is goodness, xiIndex value f (x) with index number ii) For the access probability, k, m, and n are positive integers.
Thus, if the quality and the quality are higher, the service evaluation result is better, that is, the network access quality is higher. Conversely, the worse the service evaluation result, the worse the network access quality.
Further, the server further performs specific positioning on the poor quality network element, and the specific steps of the poor quality network element positioning are as follows:
s511, the server determines the network element corresponding to each index value not greater than the preset index threshold according to the incidence relation between the network elements and the index values contained in the monitoring data.
S512, the server executes the following steps for each determined network element respectively:
screening all access records of the network element in the monitoring data, determining the access times of each index value with the index value not greater than a preset index threshold value and the total access times of the network element according to the screened access records, and further determining the quality difference rate of the network element according to the determined access times and the total access times.
S513, determining the quality difference network elements according to the quality difference rate of each network element.
Specifically, the server screens a set number of network elements with the highest quality difference rate from the network elements according to the quality difference rate, and determines the network elements as the quality difference network elements.
Therefore, the poor quality network element can be positioned, and further detailed analysis and optimization processing can be performed on the poor quality network element.
The above embodiments are described below with a specific application scenario.
Table 1.
Referring to table 1, an exemplary table of download rate statistics is shown, which includes each download rate, and corresponding access times, accumulated times, and access probability. The server filters each index value to obtain a filtering set containing 303 effective index values.
Fig. 2e is a diagram illustrating an example of service evaluation. The server sets the preset index threshold value to be 1000kbps, and determines the quality difference rate to be 39.65% and the quality ratio to be 60.35% according to the access probability of each index value after screening.
Fig. 2f is a diagram illustrating an example of the quality difference IP. Including resource IP, address affiliation, corresponding domain name, and quality of service rate. Wherein, the resource IP is a home address IP. The server acquires each resource IP with the downloading speed lower than 1000kbps, and each resource IP comprises: 110.96.39.212, 111.13.180.108, and 111.13.180.107. And the server determines the corresponding quality difference rate according to the access times of each resource IP and the quality difference access times when the download rate is lower than 1000 kbps. 110.96.39.212 had a mass difference of 51.89%, 111.13.180.108 had a mass difference of 28.45%, and 111.13.180.107 had a mass difference of 28.58%. The server determines 110.96.39.212 a quality difference IP according to the quality difference rate of each resource IP.
Further, after the server determines the quality difference IP, detailed analysis can be performed on the quality difference reason of the quality difference IP from the time dimension and the content dimension according to the corresponding domain name of the quality difference IP, and network optimization can be performed.
Optionally, the domain name may be analyzed to determine the poor quality domain name, and the cause of the poor quality domain name may be analyzed according to the poor quality time period of the poor quality domain name and the resource caching status of the poor quality domain name.
In the embodiment of the application, the abnormal value can be removed, the effective index value can be screened out, the influence of subjective factors and extreme values on a service evaluation result is avoided, the quality difference rate and the quality merit rate are determined according to the screened effective index value, the user perception aiming at the service can be reflected more objectively and directly, and the method and the device can be used for mass data analysis and quality analysis aiming at single limited data and indexes.
In the embodiment of the application, only one index is taken as an example for explanation, in practical application, corresponding service evaluation results can be determined respectively for different indexes, and then a comprehensive service evaluation result is determined according to each obtained service evaluation result.
In an embodiment of the present application, an electronic device includes: one or more processors;
and one or more computer-readable media having stored thereon a program for business evaluation, wherein the program, when executed by one or more processors, performs the steps in the above-described embodiments.
In an embodiment of the present application, one or more computer-readable media having stored thereon a program for service evaluation, where the program, when executed by one or more processors, causes a communication device to perform the steps in the above-described embodiments.
Based on the same inventive concept, the embodiment of the present application further provides a service evaluation apparatus, and as the principle of the apparatus and the device for solving the problem is similar to that of a service evaluation method, the implementation of the apparatus can refer to the implementation of the method, and repeated details are omitted.
As shown in fig. 3, which is a schematic structural diagram of a service evaluation apparatus provided in the embodiment of the present application, the service evaluation apparatus includes:
an obtaining unit 30, configured to obtain monitoring data of network access of a user, where the monitoring data includes an index value of each network access;
a counting unit 31, configured to count access times corresponding to each index value according to each index value included in the monitoring data, and determine an access probability corresponding to each index value according to the access times corresponding to each index value;
a determination unit 32, configured to determine a first sum of access probabilities corresponding to index values greater than a preset index threshold, and a second sum of access probabilities corresponding to index values not greater than the preset index threshold;
an obtaining unit 33, configured to obtain a service evaluation result according to a ratio of the first sum to the second sum.
Preferably, the statistical unit 31 is further configured to:
screening the index values according to the access probability corresponding to the index values to obtain a screening set;
and respectively determining the new access probability of each index value in the screening set according to the access times of the index values in the screening set.
Preferably, the statistical unit 31 is further configured to: sequencing the corresponding index values according to the sequence of the access probability from high to low;
setting the initial cumulative probability to be 0, and respectively executing the following steps aiming at each index value according to the sequence until the obtained cumulative probability is higher than a preset threshold value: and determining the sum of the access probability corresponding to one index value and the current cumulative probability as a new cumulative probability, and adding the index value into the set screening set.
Preferably, the obtaining unit 33 is further configured to:
screening out network elements corresponding to index values which are not greater than a preset index threshold value according to the incidence relation between each network element and the index value which is also contained in the monitoring data;
respectively aiming at each screened network element, executing the following steps: determining the quality difference rate of a network element according to the access times of all index values of the network element, which are not more than a preset index threshold, and the total access times corresponding to the network element;
and determining the quality difference network elements according to the quality difference rate of each network element.
In the service evaluation method, the service evaluation device, the terminal device and the medium provided by the embodiment of the application, monitoring data of user network access is obtained, and the monitoring data comprises index values of each network access; respectively counting the access times corresponding to each index value according to each index value contained in the monitoring data, and respectively determining the access probability corresponding to each index value according to the access times corresponding to each index value; determining a first sum of access probabilities corresponding to index values larger than a preset index threshold value and a second sum of access probabilities corresponding to index values not larger than the preset index threshold value; and obtaining a service evaluation result according to the ratio of the first sum to the second sum. Therefore, the probability distribution area corresponding to each index value is divided according to the preset index threshold, and the service evaluation result is obtained according to each divided access probability, so that the accuracy of the service evaluation result of the user is improved.
For convenience of description, the above parts are separately described as modules (or units) according to functional division. Of course, the functionality of the various modules (or units) may be implemented in the same one or more pieces of software or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (7)
1. A method for service evaluation, comprising:
acquiring monitoring data of user network access, wherein the monitoring data comprises an index value of each network access;
respectively counting the access times corresponding to each index value according to the index values contained in the monitoring data, and respectively determining the access probability corresponding to each index value according to the access times corresponding to each index value, wherein the access probability corresponding to each index value is determined according to the ratio of the access times of each index value to the sum of the access times corresponding to all the index values;
determining a first sum of access probabilities corresponding to index values larger than a preset index threshold value and a second sum of access probabilities corresponding to index values not larger than the preset index threshold value;
and obtaining a service evaluation result according to the ratio of the first sum to the second sum.
2. The method of claim 1, wherein after determining the access probability corresponding to each metric value separately, before determining the first sum of the access probabilities corresponding to the metric values greater than a preset threshold, the method comprises:
screening the index values according to the access probability corresponding to the index values to obtain a screening set;
and respectively determining the new access probability of each index value in the screening set according to the access times of the index values in the screening set.
3. The method of claim 2, wherein the screening of each index value according to the access probability corresponding to each index value to obtain a screening set comprises:
sequencing the corresponding index values according to the sequence of the access probability from high to low;
setting the initial cumulative probability to be 0, and respectively executing the following steps aiming at each index value according to the sequence until the obtained cumulative probability is higher than a preset threshold value: and determining the sum of the access probability corresponding to one index value and the current cumulative probability as a new cumulative probability, and adding the index value into the set screening set.
4. The method of any one of claims 1-3, further comprising:
screening out network elements corresponding to index values which are not greater than the preset index threshold value according to the incidence relation between each network element and the index value also contained in the monitoring data;
respectively aiming at each screened network element, executing the following steps: determining the quality difference rate of a network element according to the access times of all index values of the network element, which are not greater than the preset index threshold, and the total access times corresponding to the network element;
and determining the quality difference network elements according to the quality difference rate of each network element.
5. A traffic assessment apparatus, comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring monitoring data of user network access, and the monitoring data comprises an index value of each network access;
a counting unit, configured to count access times corresponding to each index value according to each index value included in the monitoring data, and determine an access probability corresponding to each index value according to the access times corresponding to each index value, where the access probability corresponding to each index value is determined according to a ratio between the access times of each index value and a sum of access times corresponding to all index values;
the determining unit is used for determining a first sum of access probabilities corresponding to the index values which are greater than a preset index threshold value and a second sum of access probabilities corresponding to the index values which are not greater than the preset index threshold value;
and the obtaining unit is used for obtaining a service evaluation result according to the ratio of the first sum to the second sum.
6. A terminal device, comprising at least one processing unit and at least one memory unit, wherein the memory unit stores a computer program which, when executed by the processing unit, causes the processing unit to carry out the steps of the method according to any one of claims 1 to 4.
7. A computer-readable medium, in which a computer program executable by a terminal device is stored, which program, when run on the terminal device, causes the terminal device to carry out the steps of the method according to any one of claims 1 to 4.
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