CN110689211A

CN110689211A - Method and device for evaluating website service capability

Info

Publication number: CN110689211A
Application number: CN201810724224.5A
Authority: CN
Inventors: 董卓达
Original assignee: Beijing Gridsum Technology Co Ltd
Current assignee: Beijing Gridsum Technology Co Ltd
Priority date: 2018-07-04
Filing date: 2018-07-04
Publication date: 2020-01-14

Abstract

The invention discloses a method and a device for evaluating website service capability, which relate to the technical field of networks, and the method comprises the following steps: acquiring a judgment index tree corresponding to a target website, wherein a root node in the judgment index tree represents the website service capability, and each other node corresponds to a judgment index; acquiring evaluation data corresponding to each leaf evaluation index in an evaluation index tree from a target website, wherein the evaluation data are website contents corresponding to the evaluation points of the corresponding leaf evaluation indexes in the target website; judging the judgment data corresponding to each leaf judgment index according to the judgment rule corresponding to each leaf judgment index to obtain the judgment score corresponding to each leaf judgment index; and counting the evaluation scores of all leaf evaluation indexes of the target website to obtain the total score of the website service capability of the target website. The method and the system are used for evaluating the service capability of the website.

Description

Method and device for evaluating website service capability

Technical Field

The invention relates to the technical field of networks, in particular to a method and a device for evaluating website service capability.

Background

With the progress of society and the popularization of networks, people pay more attention to government websites. In order to improve the credibility of the government and better serve people, the government gradually improves the internet service capability of the government. As an important tool for government Internet service capability, government websites of all levels of governments are very important. Therefore, as the basis for assessing governments at all levels, the assessment of the service capability of the website is increasingly paid attention by governments at all levels.

Currently, the website service capability needs to be evaluated by referring to the regulation in various documents issued by the center. Generally, each item of data in the government website is gradually evaluated manually according to each central requirement and regulation, and the evaluation result is obtained. However, in actual operation, when the website service capability is evaluated manually, the accuracy of data extraction in the evaluation process is poor, and the accuracy of the evaluation result is susceptible to subjectivity.

Disclosure of Invention

In view of the above problems, the present invention provides a method and an apparatus for evaluating website service capability, and mainly aims to solve the problem that in the prior art, accuracy is easily affected in a manual website service capability evaluation process, and improve accuracy of an evaluation result.

In order to solve the above technical problem, in a first aspect, the present invention provides a method for evaluating a website service capability, including:

acquiring a judgment index tree corresponding to a target website, wherein a root node in the judgment index tree represents the website service capability, and each other node corresponds to a judgment index;

acquiring evaluation data corresponding to each leaf evaluation index in an evaluation index tree from a target website, wherein the evaluation data are website contents corresponding to the evaluation points of the corresponding leaf evaluation indexes in the target website;

judging the judgment data corresponding to each leaf judgment index according to the judgment rule corresponding to each leaf judgment index to obtain the judgment score corresponding to each leaf judgment index;

and counting the evaluation scores of all leaf evaluation indexes of the target website to obtain the total score of the website service capability of the target website.

Optionally, before the obtaining of the judgment index tree corresponding to the target website, the method further includes:

extracting judgment indexes in the judgment files and the relation between the judgment indexes according to the judgment files;

constructing a judgment index tree according to the judgment indexes and the relationship between the judgment indexes; and setting a judgment rule corresponding to the judgment index according to the judgment file, wherein the judgment rule comprises a judgment standard corresponding to the judgment index and scores corresponding to different degrees meeting the judgment standard.

Optionally, before obtaining the evaluation data corresponding to each leaf evaluation index in the evaluation index tree from the target website, the method further includes:

and determining the assessment point corresponding to the leaf evaluation index according to the leaf evaluation index, wherein the assessment point is the position information of the evaluation data in the target website.

Optionally, the category of the leaf judgment indicator includes an artificial category and a machine category.

Optionally, the determining, according to the leaf evaluation index, the check point corresponding to the leaf evaluation index includes:

determining a key phrase corresponding to the leaf judgment index according to the leaf judgment index, wherein the key phrase comprises at least one keyword;

determining a candidate point location group corresponding to the key phrase from a target website according to the key phrase, wherein the candidate point location group at least comprises one candidate point location;

and determining the assessment point corresponding to the leaf evaluation index from the candidate point position grouping according to the matching degree of the key phrase and the website content of each candidate point position in the candidate point position grouping.

Optionally, if each evaluation index has an applicable website type, the obtaining of the evaluation index tree corresponding to the target website includes:

and acquiring a judgment index tree corresponding to the website type of the target website according to the website type of the target website.

Optionally, after the judging data is judged according to the judging rule to obtain the judging score corresponding to the leaf judging index, the method further includes:

receiving a sampling instruction from a second preset interface, and outputting a leaf judgment index corresponding to the sampling instruction and judgment data corresponding to the leaf judgment index according to the sampling instruction;

the counting of the evaluation scores of the leaf evaluation indexes of the target website to obtain the total score of the website service capability of the target website comprises the following steps:

when a modification instruction is received, modifying the assessment point corresponding to the leaf assessment index into an updated assessment point according to the modification instruction, re-acquiring corresponding updated assessment data according to the updated assessment point, re-determining the assessment score, and counting the total score of the website service capability of the target website after the assessment point is updated.

In a second aspect, the present invention further provides an apparatus for evaluating web site service capability, including:

the first acquisition unit is used for acquiring a judgment index tree corresponding to a target website, wherein a root node in the judgment index tree represents the service capability of the website, and each other node corresponds to one judgment index;

the second acquisition unit is used for acquiring judgment data corresponding to each leaf judgment index in the judgment index tree from a target website, wherein the judgment data are website contents corresponding to the assessment point positions of the corresponding leaf judgment indexes in the target website;

the judging unit is used for judging the judging data corresponding to each leaf judging index according to the judging rule corresponding to each leaf judging index to obtain the judging score corresponding to each leaf judging index;

and the counting unit is used for counting the judgment scores of all the leaf judgment indexes of the target website to obtain the total score of the website service capability of the target website.

Optionally, the apparatus further comprises:

the extracting unit is used for extracting judgment indexes in the judgment files and the relation between the judgment indexes according to the judgment files;

the setting unit is used for constructing a judgment index tree according to the extracted judgment indexes and the relation among the judgment indexes; and setting a judgment rule corresponding to the judgment index according to the judgment file, wherein the judgment rule comprises a judgment standard corresponding to the judgment index and scores corresponding to different degrees meeting the judgment standard.

Optionally, the apparatus further comprises:

and the determining unit is used for determining the check point position corresponding to the leaf evaluation index according to the leaf evaluation index, wherein the check point position is the position information of the evaluation data in the target website.

Optionally, the determining unit includes:

the first determining module is used for determining a keyword group corresponding to the leaf judgment index according to the leaf judgment index, wherein the keyword group comprises at least one keyword;

a second determining module, configured to determine, according to the keyword group, a candidate point location group corresponding to the keyword group from a target website, where the candidate point location group includes at least one candidate point location;

and the third determining module is used for determining the assessment point positions corresponding to the leaf evaluation indexes from the candidate point position grouping according to the matching degree of the key phrase and the website content of each candidate point position in the candidate point position grouping.

Optionally, each evaluation indicator has an applicable website type, and the first obtaining unit includes:

and the acquisition module is used for acquiring the judgment index tree corresponding to the website type of the target website according to the website type of the target website.

Optionally, the apparatus further comprises:

the receiving unit is used for receiving a sampling instruction from a second preset interface and outputting a leaf judgment index corresponding to the sampling instruction and judgment data corresponding to the leaf judgment index according to the sampling instruction;

the statistical unit comprises:

and the modification module is used for modifying the assessment point corresponding to the leaf assessment index into an updated assessment point according to the modification instruction when receiving the modification instruction, re-acquiring corresponding updated assessment data according to the updated assessment point, re-determining the assessment score and counting the total score of the website service capability of the target website after the assessment point is updated.

In order to achieve the above object, according to a third aspect of the present invention, there is provided a storage medium including a stored program, wherein when the program runs, a device in which the storage medium is located is controlled to execute the above method for evaluating web service capability.

In order to achieve the above object, according to a fourth aspect of the present invention, there is provided a processor for executing a program, wherein the program executes the method for evaluating web service capability described above.

By means of the technical scheme, the method and the device for evaluating the website service capability provided by the embodiment of the invention solve the problems that in the prior art, when the website service capability is evaluated manually, the workload is large, the time consumption is long, the subjectivity influence exists, and the accuracy of the evaluation result is easily influenced. In addition, according to the method and the device, the leaf judgment data corresponding to the leaf judgment indexes are obtained from the target website, the leaf judgment data are judged according to the preset judgment rules, the evaluation function of judging scores according to different judgment indexes can be realized for the target website, the total score of the website service capability of the target website is further obtained, the evaluation of the government service capability can be realized in a quantitative mode, the subjective influence of a manual evaluation mode on the evaluation result is avoided, and the total score obtaining process of the website service capability can be traced.

The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

FIG. 1 is a flow chart of a method for evaluating web site service capability according to an embodiment of the present invention;

FIG. 2 is a flow chart of another method for evaluating web site service capability provided by an embodiment of the invention;

FIG. 3 is a block diagram illustrating an apparatus for evaluating web site service capability according to an embodiment of the present invention;

fig. 4 is a block diagram illustrating another apparatus for evaluating web service capability according to an embodiment of the present invention.

Detailed Description

Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

In order to improve the accuracy of the evaluation of the website service capability, an embodiment of the present invention provides a method for evaluating the website service capability, as shown in fig. 1, the method includes:

101. and acquiring a judgment index tree corresponding to the target website.

In the embodiment of the invention, the target website can be government websites of all levels of governments. Since the government websites have the requirements of citizens and service, the supervision department needs to perform regular evaluation on websites of all levels of governments to determine that the operation of the websites can meet the requirements of the citizens and meet various regulations made by the center. Based on this, the target website has evaluation indexes corresponding to various regulations and requirements in the evaluation process, for example, the "service provision capability" of the government website is one evaluation index of the government website in the evaluation process. Therefore, before evaluating the service capability of the target website, a plurality of evaluation indexes, namely, the evaluation index tree in the embodiment of the present invention, required for evaluating the service capability of the target website needs to be obtained first. And the root node in the evaluation index tree represents the service capability of the website, and each other node corresponds to one evaluation index.

102. And acquiring judgment data corresponding to each leaf judgment index in the judgment index tree from the target website.

In the target website, different website contents exist, and each leaf evaluation index in the evaluation index tree corresponds to a part of website contents of the target website, namely the evaluation data in the embodiment of the invention. The evaluation data can be understood as the website content of the assessment point corresponding to the leaf evaluation index. The checkpoint may be understood as a certain web page of a fixed level in the website, for example, a certain web page corresponding to a first level of the website, or a certain web page of a second or third level of the website. Specifically, the checkpoint may be a URL address. The URL (Uniform resource Locator, URL for short) is a concise representation of the location and access method of a resource available from the internet, and is an address of a standard resource on the internet. Each file on the internet has a unique URL that contains information indicating the location of the file and how the browser should handle it. The specific position in the website can also be understood as the website addresses of different levels in the website, and certainly, the assessment point is not specifically limited and can be set according to actual needs.

It should be noted that the evaluation data corresponding to the check point needs to meet the requirement of reflecting the corresponding leaf evaluation index, so as to avoid the influence of the check point error on the accuracy of the obtained evaluation data. For example, when the leaf evaluation indicator is the responsibility list, the obtained evaluation data is the web page content of the webpage corresponding to the leaf evaluation indicator responsibility list.

103. And judging the judgment data corresponding to each leaf judgment index according to the judgment rule corresponding to each leaf judgment index to obtain the judgment score corresponding to each leaf judgment index.

After the evaluation data is obtained in the previous step 102, the evaluation data can be evaluated according to a preset evaluation rule. In the embodiment of the present invention, the evaluation rule is set according to an evaluation file corresponding to the target website, the evaluation file may be one or more file information such as a file, a notification, a letter and the like issued by an organization such as a state institute or a shared central office, the evaluation file includes a construction requirement for a website of government affairs services and public affairs, and each evaluation index for evaluating website service capability is provided. The evaluation document defines each evaluation index and the relationship between each evaluation index, for example: a judgment index is composed of which sub-level judgment indexes. The evaluation file also explicitly defines evaluation rules for some evaluation indexes, which may include evaluation criteria and corresponding scores, and explicitly makes specific quantitative requirements for the evaluation indexes.

Therefore, according to the method in the step, the score corresponding to the evaluation data can be searched in the evaluation rule, and the evaluation score can be further obtained. Of course, in the embodiments of the present invention, including but not limited to the above-mentioned evaluation method, a score comparison table preset in the evaluation rule may also be used, where the score comparison table includes scores corresponding to different degrees that are satisfied by the evaluation data corresponding to each leaf evaluation index, and then the obtained evaluation data is matched with the table to obtain the evaluation score corresponding to the leaf evaluation index. Here, the evaluation method is not limited, and may be set in advance as needed.

104. And counting the judgment scores of all leaf judgment indexes of the target website to obtain the total score of the website service capability of the target website.

Since the web site service capability includes a plurality of different leaf evaluation indexes, in the embodiment of the present invention, the target web site may be respectively evaluated based on the different leaf evaluation indexes according to the method in step 103, so as to obtain the evaluation scores corresponding to the different leaf evaluation indexes. Then, according to the method in this step, the total score of the website service capability of the target website is obtained by counting the plurality of leaf evaluation scores. Of course, the total score may be obtained by adding up the plurality of leaf evaluation scores obtained in the foregoing step 103. Of course, the weight coefficients of all nodes except the root node of the evaluation index tree can be obtained, and then the total score of the website service capability is calculated according to the structure of the evaluation index tree based on the evaluation scores of different leaf evaluation indexes. Of course, in the embodiment of the present invention, the calculation manner of the total score of the website service capability of the target website is not specifically limited, and a manner of counting the total score may be selected according to actual needs.

According to the method for evaluating the website service capability provided by the embodiment of the invention, the problems that in the prior art, when the website service capability is evaluated manually, the workload is large, the time consumption is long, and the accuracy of the evaluation result is easily influenced due to subjectivity influence exist are solved. In addition, according to the method and the device, the leaf judgment data corresponding to the leaf judgment indexes are obtained from the target website, the leaf judgment data are judged according to the preset judgment rules, the evaluation function of judging scores according to different judgment indexes can be realized for the target website, the total score of the website service capability of the target website is further obtained, the evaluation of the government service capability can be realized in a quantitative mode, the subjective influence of a manual evaluation mode on the evaluation result is avoided, and the total score obtaining process of the website service capability can be traced.

Further, as a refinement and an extension of the embodiment shown in fig. 1, the embodiment of the present invention further provides another method for evaluating a website service capability, as shown in fig. 2, the method specifically includes the following steps:

201. and extracting the evaluation indexes in the evaluation file and the relationship between the evaluation indexes according to the evaluation file.

Because the website service capability is determined according to various requirements and instructions issued by the center and the website service capability comprises various different capabilities, based on the method and the device, the relationship between each judgment index in the judgment file and the judgment index can be extracted firstly. The evaluation document in the embodiment of the present invention is consistent with the description in step 102 in the foregoing embodiment, and will not be discussed here.

Because the evaluation file can contain various different instructions or files, when the file sent by the center is changed or a new instruction or requirement is added, the evaluation index corresponding to the target website can be updated according to the updating of the evaluation file. Therefore, according to the method in the step, the judgment indexes in the judgment files are extracted through the judgment files, and the judgment indexes can be timely modified and updated when the judgment files are changed or updated, so that the accuracy of subsequent evaluation results is improved.

202', according to the judgment indexes and the relationship between the judgment indexes, constructing a judgment index tree.

After the evaluation indexes in the evaluation file and the relations among the evaluation indexes are extracted, the evaluation index tree can be constructed according to the evaluation indexes and the relations among the evaluation indexes.

Since the website has a plurality of website types (such as government, public security, hospital, school, etc.), the types of the websites to which each judgment index extracted from the judgment document is applied are different, and therefore each judgment index has the applicable website type. The type of the website suitable for each evaluation index can be marked in a mode of attributes or labels and the like.

This step can be achieved in at least two ways:

1. and constructing a judgment index tree for each website type.

For one website type, step 202' may include: and constructing a judgment index tree of the website type according to the judgment index of the website type and the relation between the judgment indexes. Specifically, the judgment indexes and the relations among the judgment indexes suitable for the website type can be continuously spliced and constructed along with the extraction of the judgment indexes and the relations among the judgment indexes, and the splicing construction can be carried out after all the judgment indexes and the relations among the judgment indexes suitable for the website type are extracted, so that the realization of the judgment index tree in the embodiment of the invention is not influenced.

Each judgment index in the judgment index tree can have a preset weight coefficient, and a subsequent user can adjust the weight coefficient according to actual needs.

All leaf evaluation indexes of the evaluation index tree have evaluation rules, one leaf evaluation index corresponds to one evaluation rule (corresponding to an applicable website type), and other nodes do not. For the evaluation indexes without the evaluation documents referring to the corresponding evaluation contents and the sub-level evaluation indexes, the evaluation score can not be carried out, and an empty leaf node can be established for the node of the evaluation index in the evaluation index tree.

After the judgment index trees of each website type are constructed, the judgment index trees with the same structure can be further combined, so that the number of the judgment index trees needing to be maintained is reduced.

2. And constructing a total evaluation index tree for all the website types.

In this case, the evaluation indexes in all the evaluation files are extracted, and the relationship between the evaluation indexes is extracted. Step 202' may include: and constructing a total judgment index tree according to the judgment indexes and the relation between the judgment indexes, wherein each judgment index has an applicable website type. Specifically, the judgment indexes and the relations among the judgment indexes can be continuously spliced and constructed along with the extraction of the judgment indexes, the splicing construction can be carried out after all the judgment indexes and the relations among the judgment indexes are extracted, and all the judgment index trees can be integrated after the judgment index trees of various website types are obtained by using the mode 1, so that the realization of the total judgment index tree in the embodiment of the invention is not influenced. The root node of the total evaluation index tree still represents the service capability of the website, and each other node corresponds to one evaluation index.

202. And setting a judgment rule corresponding to the judgment index according to the judgment file.

The evaluation rule comprises an evaluation standard corresponding to the evaluation index and each score corresponding to each degree meeting the evaluation standard.

Since the evaluation file contains at least one file or indication for determining the service capability of the evaluated website, the evaluation file specifies evaluation rules for some evaluation indexes besides the evaluation indexes and the relationship among the evaluation indexes, and the evaluation rules may include evaluation criteria and corresponding scores. Therefore, in the embodiment of the present invention, it is necessary to set a judgment rule for the judgment index extracted in the step 201 according to the judgment file, wherein the judgment rule includes a judgment standard for the judgment index and scores corresponding to different degrees meeting the judgment standard. Here, since the web service capabilities include a plurality of capabilities corresponding to different evaluation indexes, the capability reflection modes are different, and the evaluation of each capability in the evaluation file is different, the evaluation rules corresponding to the different evaluation indexes are also different to a certain extent in this step, and the evaluation rules can be set according to actual needs.

Therefore, the judgment rule corresponding to the judgment index is set through the judgment file, a scientific judgment basis is provided for subsequent judgment, the accuracy of the evaluation result is ensured, in addition, the judgment standard is set in the judgment rule, and the scores corresponding to different degrees according with the judgment standard are respectively set, so that the judgment result can be obtained quantitatively in the subsequent judgment process, and the judgment result is more accurate and visual.

Steps 202 and 202' may be executed sequentially or in parallel, and the execution order of these two steps does not affect the implementation of the subsequent process.

The judgment rule of the judgment index can be associated to the judgment index tree/the total judgment index tree, and can also be stored with the judgment index tree/the total judgment index tree respectively.

203. And acquiring a judgment index tree corresponding to the target website.

Corresponding to the two ways in step 202', there are also two ways to obtain the evaluation index tree corresponding to the target website:

1. and acquiring a judgment index tree corresponding to the website type of the target website according to the website type of the target website.

Because the judgment index trees of various website types are constructed in advance, the judgment index trees corresponding to the website types of the target websites can be obtained by using the website types of the target websites.

2. And acquiring a judgment index tree corresponding to the website type of the target website from the total judgment index tree according to the website type of the target website.

The total evaluation index tree is obtained by carrying out similar combination on the evaluation indexes of all the evaluation files and the relationship among the evaluation indexes, wherein each evaluation index carries an applicable website type when being stored, so that the evaluation index tree corresponding to the website type of the target website can be extracted from the total evaluation index tree according to the website type of the target website.

The evaluation index tree in this manner is different from the total evaluation index tree:

the total evaluation index tree integrates evaluation indexes of all evaluation files, so that each evaluation index in the total evaluation index tree is suitable for at least one website type (such as one or more of government, public security, hospital and the like), more than one evaluation rule of one evaluation index is possible, each website type corresponds to one evaluation rule, and the weight coefficient of the evaluation index corresponding to each website type can be stored together with the evaluation rules. The same evaluation index may be a leaf evaluation index for one website type, and may be a non-leaf evaluation index for another website type, and there is a sub-level evaluation index below the same evaluation index, because the evaluation document specifies whether the sub-level evaluation index is related to the evaluation index of the different website type. In addition, whether the evaluation index has an evaluation rule or not is related to whether the content specified by the evaluation index by the evaluation file relates to the evaluation content or not, if so, the evaluation rule can be set for the evaluation index related to the content, and if not, the evaluation rule cannot be set for the evaluation index mentioned by the content.

The evaluation index tree is extracted from the total evaluation index tree according to the website type of the target website, all leaf evaluation indexes of the evaluation index tree have evaluation rules, one leaf evaluation index corresponds to one evaluation rule (corresponding to the target website type), and other nodes do not exist. For the evaluation indexes without the evaluation file referring to the corresponding evaluation content and the sub-level evaluation indexes, an empty leaf node can be established for the node of the evaluation index in the evaluation index tree.

204. And determining the assessment point positions corresponding to the leaf assessment indexes according to the leaf assessment indexes.

In the embodiment of the present invention, the description of the checkpoint is the same as that in step 102 in the foregoing embodiment, and details are not repeated here.

Furthermore, because the evaluation data corresponding to some evaluation points may have differences in subjective degrees, the evaluation index for evaluating the website service capability is also affected by the subjective degree, wherein the subjective degree is used to determine the interference degree of human subjective factors in the evaluation data corresponding to the evaluation index on the evaluation result, and the categories of the evaluation index in the embodiment of the present invention may include manual categories and machine categories based on different subjective degrees. Because the leaf evaluation indexes of the evaluation index tree of the target website relate to the problem of determining the evaluation point positions, the categories of the leaf evaluation indexes of the evaluation index tree can comprise an artificial category and a machine category. The total evaluation index tree can be regarded as the integration of the evaluation index trees of all the website types, so that all the leaf evaluation indexes and a part of the non-leaf evaluation indexes can be provided with the categories of the evaluation indexes.

For the condition that the judgment index also has the judgment index category, the judgment index can be stored with the judgment index category when being stored, and the judgment index category can be marked in the modes of attributes, labels and the like. The type of the judgment index can be marked in the same or different form as the type of the applicable website, and the implementation of the embodiment of the invention is not influenced.

Therefore, based on different subjective degrees of the evaluation index, the method specifically comprises the following steps: firstly, determining the category of the evaluation index according to the subjective degree of the evaluation index. And then determining the assessment points of the assessment indexes according to the assessment index categories.

In the embodiment of the invention, the subjective degree is used for determining the interference degree of the human subjective factors in the evaluation data corresponding to the evaluation index on the evaluation result. Since the service capability of the website specified by the country includes a plurality of capabilities, the manner of determining the evaluation data partially reflecting the capabilities is not simply determining whether the data exists or not and whether the data meets the conditions, but needs subjective analysis by people to determine the specific meaning of the evaluation data, such as: the evaluation data corresponding to the crowd feedback in the assessment points are not simply identifiable by a machine, but need to be analyzed and participated in manually. Therefore, the types of the evaluation indexes can be classified based on the subjective degree, one is an evaluation index of a machine type which is easily recognized and acquired by a machine, and one is an evaluation index of a manual type which needs manual analysis and input. It should be noted that, in the embodiment of the present invention, the determination process of the subjective degree of the evaluation index and the manner of identifying the type of the evaluation index as a machine type or an artificial type may be determined based on an artificial manner, and a manually preset index tag may be used to identify different evaluation indexes.

For example, for the service response capability in the service capability of the website, many of the capabilities need to be determined from the left message of the user browsing the website, so for such evaluation indexes, the input of evaluation data is required to be performed manually in the evaluation process, and such evaluation indexes are just artificial categories in the evaluation indexes determined according to the subjectivity described in the embodiment of the present invention.

Here, when the evaluation index is determined to be an artificial category, and when the point location corresponding to the evaluation index is determined, because the subjectivity of the evaluation data corresponding to the index is high, the recognition of the point location and the acquisition of the evaluation data by the machine are poor, and errors are prone to occur, therefore, the point location determined in an artificial mode can be received as the point location of the index, or data input by a user can be directly received as the evaluation data through a preset interface program.

Further, in this step, when the evaluation index is determined to be of the machine type, it may be determined that the influence of subjective factors in the data content of the evaluation index of the type is small, and the corresponding evaluation data may be obtained by the machine, specifically, before the evaluation data is obtained, the assessment point location needs to be determined first, specifically, the determination of the assessment point location may be performed specifically according to the following steps: firstly, according to the evaluation index, determining a keyword group corresponding to the evaluation index and a combination relationship among keywords in the keyword group, where the keyword group includes at least one keyword, and in an embodiment of the present invention, the combination relationship among the keywords may be represented by a regular expression, for example: when the keyword group includes industrial injury, labor capacity, identification and identification, the combination relationship among the keywords can be expressed according to a regular expression 'industrial injury/labor capacity + identification/identification'. Then, according to the key phrase, determining a candidate point location group corresponding to the key phrase from the target website, wherein the candidate point location group at least comprises one candidate point location. And finally, determining the assessment points corresponding to the evaluation indexes from the candidate point position grouping according to the matching degree of the key phrases and the website content of each candidate point position in the candidate point position grouping. For example, the candidate point location with the matching degree greater than or equal to the preset threshold and the highest matching degree value may be screened out as the check point location of the evaluation index.

In addition, in the embodiment of the present invention, after the assessment point of the assessment index is determined, the keyword may be extracted again from the assessment point, and a new combination relationship may be constructed using the newly extracted keyword and the original keyword, for example, a new regular expression constructed according to a new keyword group, and the re-extracted keyword is added to the keyword group, so as to further supplement and update the keyword group and the combination relationship between the keywords of the assessment index, and then when the assessment point is determined again in the following, the matching efficiency may be improved, and the accuracy of determining the assessment point may be further improved.

The classification of the evaluation index is determined according to the subjective degree of the evaluation index, and the assessment point of the evaluation index is determined according to the classification of the evaluation index, so that the classification of the manual classification and the machine classification in the evaluation index can be realized, the problem that the acquired data is inaccurate when part of assessment points needing manual input of evaluation data are acquired by a machine is solved, and data guarantee is provided for subsequent evaluation. And determining a key phrase corresponding to the evaluation index according to the evaluation index, determining a candidate point position group corresponding to the key phrase from a target website, and determining a check point position corresponding to the evaluation index from the candidate point position group according to the matching degree of the key phrase and the website content of each candidate point position in the candidate point position group, so as to guarantee the accuracy of the check point position and further provide guarantee for the accuracy of subsequent evaluation data.

205. And acquiring judgment data corresponding to each leaf judgment index in the judgment index tree from the target website.

The evaluation data is website content corresponding to the evaluation point positions of the corresponding leaf evaluation indexes in the target website;

the descriptions of the target website, the leaf evaluation index and the evaluation data in the embodiment of the present invention are consistent with the description in the step 102, and are not repeated herein.

Based on the method in step 204, after the evaluation index tree corresponding to the target website is obtained, since the leaf evaluation index has two types, namely, an artificial type and a machine type, in this step, on one hand, when the type of the leaf evaluation index is an artificial type, the obtaining of the evaluation data corresponding to the leaf evaluation index from the target website may specifically be: and receiving manually input evaluation data corresponding to the leaf evaluation index through a first preset interface.

On the other hand, when the category of the leaf evaluation index is a machine category, the obtaining of the evaluation data corresponding to the leaf evaluation index from the target website may specifically be: and crawling judgment data corresponding to the check point positions of the leaf judgment indexes through a machine crawler.

Therefore, on one hand, when the category of the leaf evaluation index is an artificial category, the evaluation data corresponding to the manually input evaluation index is received through the first preset interface, the problem that the evaluation data obtained through a machine is inaccurate can be avoided, and the accuracy of a subsequent evaluation result is improved. On the other hand, when the category of the leaf evaluation index is a machine category, the evaluation data corresponding to the assessment point of the evaluation index is crawled by a machine crawler, so that the comprehensiveness of the obtained evaluation data is ensured, the accuracy of a subsequent evaluation result is improved, manual operation is not needed, the labor cost is saved, and the evaluation efficiency is high.

206. And judging the judgment data corresponding to each leaf judgment index according to the judgment rule corresponding to each leaf judgment index to obtain the judgment score corresponding to each leaf judgment index.

According to the method described in step 205, the evaluation rule includes the evaluation criterion and the scores corresponding to different degrees of the evaluation criterion, so in this step, the matching operation can be performed according to the obtained evaluation data and the evaluation rule, and the score corresponding to the evaluation data is the evaluation score of the leaf evaluation index corresponding to the target website.

For example, when the leaf evaluation index "responsibility list" is evaluated, the obtained evaluation data of the assessment points includes 20, 16 of which meet the requirements, 4 of which do not meet the requirements, and 20 of which meet the requirements according to the "responsibility list" evaluation standard in the preset evaluation rule. Meanwhile, the degree and the corresponding score meeting the judgment standard are respectively as follows: the number of 20 qualified products is 10 minutes; 17-19 strips meet the requirement of 9 minutes; the number of the 14-16 strips is 8 according to the requirement; the number of the 13 or less is 0 min. Then according to the method described in this step, it can be determined that 16 compliance requirements correspond to 8 points, and the government website has a judgment score of 8 points corresponding to the "responsibility list" leaf judgment index.

207. And receiving the sampling instruction from the second preset interface, and outputting a leaf judgment index corresponding to the sampling instruction and judgment data corresponding to the leaf judgment index according to the sampling instruction.

Because the accuracy of the evaluation point corresponding to the leaf evaluation index affects the accuracy of the evaluation data corresponding to the point, in the embodiment of the invention, in the process of evaluating the website service capability, the user can also determine whether the current evaluation data can correspond to the leaf evaluation index by outputting the evaluation data corresponding to the leaf evaluation index, thereby ensuring the accuracy of the subsequent evaluation result. Specifically, the method further comprises the following steps: according to the received spot-check instruction, determining the leaf evaluation index required to be subjected to spot-check according to the spot-check instruction, and then outputting the leaf evaluation index, the corresponding evaluation data and the corresponding evaluation score, so that a user can intuitively know how the evaluation score corresponding to each leaf evaluation index is obtained in the current website service capability evaluation process, and then the evaluation scores of different evaluation indexes in the current website service capability evaluation process are traced, thereby providing guarantee for the accuracy of the statistical result of the subsequent evaluation total score,

therefore, by receiving the sampling instruction from the second preset interface and outputting the leaf judgment index corresponding to the sampling instruction and the judgment data corresponding to the leaf judgment index according to the sampling instruction, a user can confirm the judgment data corresponding to different leaf judgment indexes, the verification function of the judgment data corresponding to each leaf judgment index is realized, and the accuracy of obtaining the judgment data of the judgment data during evaluation is further ensured.

208. And counting the judgment scores of all leaf judgment indexes of the target website to obtain the total score of the website service capability of the target website.

In this step, the process and manner of performing total score statistics according to the multiple evaluation scores of different leaf evaluation indexes of the target website are consistent with the description in step 104 in the foregoing embodiment, and are not described herein again.

In the embodiment of the invention, because the structures of the judgment index trees of different website types are different, the total scores of the statistical website service capabilities of different judgment index tree structures can also be different.

When the evaluation index tree in the target website only has one level except for the root node, the total score of the website service capability of the target website is counted, and the evaluation scores of all leaf evaluation indexes of the target website can be accumulated to obtain the total score. Of course, statistics may also be performed through each evaluation score and its corresponding weight value based on the weights of different leaf evaluation indicators.

When the evaluation index tree in the target website comprises a plurality of levels besides the root node, when the total website service capability is counted, the evaluation score of each evaluation index in the adjacent upper level can be counted according to the evaluation score of each leaf evaluation index in the lowest level, and the process is analogized layer by layer, and finally, the evaluation score corresponding to the root node is counted and recorded as the total website service capability score. Here, the statistical manner of the total website service capability score and the evaluation score of the evaluation index of each level is not limited herein, and the statistical manner may be selected according to the actual evaluation index tree structure of the target website.

For example, the tree of evaluation indexes in the target website includes three levels besides the root node, one primary evaluation index includes at least one secondary evaluation index, one secondary evaluation index includes at least one tertiary evaluation index, after the evaluation score of each tertiary evaluation index (i.e., each evaluation index of the lowest level) is obtained, the evaluation score of each secondary evaluation index is the statistical score of the evaluation scores of each tertiary evaluation index included in the secondary evaluation index, the evaluation score of each primary evaluation index is the statistical score of the evaluation scores of each secondary evaluation index included in the primary evaluation index, and finally the total website service capability score of the target website is the statistical score of the evaluation scores of each primary evaluation index.

In addition, as several judgment indexes of the same level, some of the judgment indexes may include the judgment index of the next adjacent level, and some of the judgment indexes may be leaf judgment indexes; moreover, one leaf judgment index can also belong to more than two upper-level judgment indexes; when the same leaf evaluation index belongs to different upper evaluation indexes, the levels of the different upper evaluation indexes can be the same or different. The specific structure of the judgment index tree can be determined.

Further, based on the method described in step 207, since the corresponding leaf evaluation index and the corresponding evaluation data are output according to the sampling instruction, the user can determine whether the evaluation data corresponds to the leaf evaluation index, and modify or determine the point location based on the determination result, so as to ensure that the obtained evaluation data can correspond to the leaf evaluation index, thereby ensuring the accuracy of the evaluation result.

When the user determines that the leaf evaluation index corresponds to the evaluation data, the point position of the evaluation data currently evaluating the leaf evaluation index is accurate, namely the point position is not abnormal, and therefore the user can issue a confirmation instruction.

When the user finds that the evaluation data fed back in the step 207 is not the data required by the leaf evaluation index, it indicates that the check point location corresponding to the current leaf evaluation index is abnormal or inaccurate or the website page is updated, the user will issue a modification instruction so as to re-input a new check point location through the user to modify the check point location, and in this case, the step may specifically be: when a modification instruction is received, modifying the assessment point corresponding to the leaf assessment index into an updated assessment point according to the modification instruction, re-acquiring corresponding updated assessment data according to the updated assessment point, re-determining the assessment score, and counting the total score of the website service capability of the target website after the assessment point is updated. In addition, when the user updates the assessment point, the system can compare the data corresponding to the updated assessment point input by the user with the data corresponding to the original assessment point, and re-extract the key word group and the combination relationship among the key words of the part of data in a machine self-learning mode so as to update the assessment point corresponding to the leaf assessment index, thereby ensuring that when the leaf assessment index is assessed again in the follow-up process, the assessment data corresponding to the assessment point can be acquired through the updated key word group and the combination relationship among the key words, and further ensuring the accuracy of the follow-up assessment result.

Therefore, according to the method in the step, when a modification instruction issued by a user is received, the assessment point corresponding to the leaf evaluation index is modified into an updated assessment point through the modification instruction, and the assessment is performed again, so that the problem that the assessment result is inaccurate due to deviation or abnormality of the assessment point can be avoided, and the accuracy is improved. And after the assessment point is updated, the combination relationship between the key phrases and the keywords is re-extracted in a machine self-learning mode, so that the new assessment point can be determined according to the updated combination relationship between the key phrases and the keywords when the leaf assessment index is assessed again subsequently, the obtained assessment data can always correspond to the leaf assessment index, and the accuracy of the assessment result of the website service capability is ensured.

Further, as an implementation of the method shown in fig. 1, an embodiment of the present invention further provides an apparatus for evaluating a website service capability, which is used to implement the method shown in fig. 1. The embodiment of the apparatus corresponds to the embodiment of the method, and for convenience of reading, details in the embodiment of the apparatus are not repeated one by one, but it should be clear that the apparatus in the embodiment can correspondingly implement all the contents in the embodiment of the method. As shown in fig. 3, the apparatus includes: a first obtaining unit 31, a second obtaining unit 32, an evaluation unit 33 and a statistic unit 34, wherein

The first obtaining unit 31 may be configured to obtain a judgment index tree corresponding to a target website, where a root node in the judgment index tree represents a website service capability, and each of other nodes corresponds to a judgment index;

the second obtaining unit 32 may be configured to obtain, from a target website, evaluation data corresponding to each leaf evaluation index in an evaluation index tree, where the evaluation data is website content corresponding to a point of a corresponding leaf evaluation index in the target website;

the evaluation unit 33 may be configured to evaluate the evaluation data corresponding to each leaf evaluation index according to the evaluation rule corresponding to each leaf evaluation index, so as to obtain an evaluation score corresponding to each leaf evaluation index;

the counting unit 34 may be configured to count the evaluation scores of the leaf evaluation indicators of the target website to obtain a total score of the website service capability of the target website.

Further, as an implementation of the method shown in fig. 2, an embodiment of the present invention further provides an apparatus for evaluating a website service capability, which is used to implement the method shown in fig. 2. The embodiment of the apparatus corresponds to the embodiment of the method, and for convenience of reading, details in the embodiment of the apparatus are not repeated one by one, but it should be clear that the apparatus in the embodiment can correspondingly implement all the contents in the embodiment of the method. As shown in fig. 4, the apparatus includes: a first obtaining unit 41, a second obtaining unit 42, an evaluation unit 43 and a statistic unit 44, wherein

A first obtaining unit 41, configured to obtain a judgment index tree corresponding to a target website, where a root node in the judgment index tree represents a website service capability, and each of other nodes corresponds to a judgment index;

the second obtaining unit 42 may be configured to obtain, from a target website, evaluation data corresponding to each leaf evaluation index in an evaluation index tree, where the evaluation data is website content corresponding to a point of a corresponding leaf evaluation index in the target website;

the evaluation unit 43 may be configured to evaluate the evaluation data corresponding to each leaf evaluation index according to the evaluation rule corresponding to each leaf evaluation index, so as to obtain an evaluation score corresponding to each leaf evaluation index;

the counting unit 44 may be configured to count the evaluation scores of the leaf evaluation indicators of the target website, so as to obtain a total score of the website service capability of the target website.

Further, the apparatus further comprises:

the extracting unit 45 may be configured to extract, according to the evaluation file, the evaluation index in the evaluation file and a relationship between the evaluation indexes;

a setting unit 46, configured to construct a judgment index tree according to the judgment indexes extracted by the extracting unit 45 and the relationship between the judgment indexes; and setting a judgment rule corresponding to the judgment index according to the judgment file, wherein the judgment rule comprises a judgment standard corresponding to the judgment index and scores corresponding to different degrees meeting the judgment standard.

Further, the apparatus further comprises:

the determining unit 47 may be configured to determine, according to the leaf evaluation index, a point location corresponding to the leaf evaluation index, where the point location is location information of evaluation data in the target website.

Further, the determining unit 47 may be specifically configured to determine a category of the evaluation index according to a subjective degree of the evaluation index, and determine the assessment point of the evaluation index according to the category of the evaluation index, where the subjective degree is used to determine an interference degree of an artificial subjective factor in evaluation data corresponding to the evaluation index on an evaluation result, and the category of the evaluation index includes an artificial category and a machine category.

The determining unit 47 further comprises:

a first determining module 471, configured to determine, according to the leaf evaluation indicator, a keyword group corresponding to the leaf evaluation indicator, where the keyword group includes at least one keyword;

a second determining module 472, configured to determine, according to the key phrase determined by the first determining module 471, a candidate point location group corresponding to the key phrase from a target website, where the candidate point location group includes at least one candidate point location;

the third determining module 473 may be configured to determine, according to the matching degree between the keyword group determined by the first determining module 471 and the website content of each candidate point in the candidate point location grouping determined by the second determining module 472, a point location corresponding to the leaf evaluation indicator from the candidate point location grouping.

Further, each evaluation index has an applicable website type, and the first obtaining unit 41 may include:

the obtaining module 410 may be configured to obtain, according to the website type of the target website, a judgment index tree corresponding to the website type of the target website.

Further, the apparatus further comprises:

the receiving unit 48 may be configured to receive a sampling instruction from a second preset interface, and output a leaf evaluation index corresponding to the sampling instruction and evaluation data corresponding to the leaf evaluation index according to the sampling instruction;

the statistical unit 44 includes:

the modifying module 440 may be configured to, when receiving a modifying instruction, modify the checkpoint position corresponding to the leaf evaluation index into an updated checkpoint position according to the modifying instruction, obtain corresponding updated evaluation data again according to the updated checkpoint position, re-determine the evaluation score, and count the total score of the website service capability of the target website after the checkpoint position is updated.

By means of the technical scheme, the embodiment of the invention provides the method and the device for evaluating the website service capability, and aims to solve the problems that in the prior art, when the website service capability is evaluated manually, the workload is large, the time consumption is long, the subjectivity influence exists, and the accuracy of an evaluation result is easily influenced. In addition, according to the method and the device, the leaf judgment data corresponding to the leaf judgment indexes are obtained from the target website, the leaf judgment data are judged according to the preset judgment rules, the evaluation function of judging scores according to different judgment indexes can be realized for the target website, the total score of the website service capability of the target website is further obtained, the evaluation of the government service capability can be realized in a quantitative mode, the subjective influence of a manual evaluation mode on the evaluation result is avoided, and the total score obtaining process of the website service capability can be traced.

Meanwhile, the judgment rules corresponding to the judgment indexes are set through the judgment indexes, so that different judgment indexes can be ensured to have corresponding judgment rules, a more scientific judgment basis is provided for subsequent judgment, the accuracy of an evaluation result is ensured, in addition, the judgment standards are set in the judgment rules, and the scores corresponding to different degrees meeting the judgment standards respectively can enable the judgment result to be obtained quantitatively in the subsequent judgment process, so that the judgment result is more accurate and visual. In addition, the classification of the evaluation index is determined according to the subjective degree of the evaluation index, and the assessment point of the evaluation index is determined according to the classification of the evaluation index, so that the classification of the manual classification and the machine classification in the evaluation index can be realized, the problem that the acquired data is inaccurate when part of assessment points needing manual input of evaluation data are acquired by a machine is solved, and data guarantee is provided for subsequent evaluation. And determining a key phrase corresponding to the evaluation index according to the evaluation index, determining a candidate point location group corresponding to the key phrase from a target website, and determining a check point location corresponding to the evaluation index from the candidate point location group according to the matching degree of the key phrase and the website content of each candidate point location in the candidate point location group, so as to guarantee the accuracy of the check point location and further provide guarantee for the accuracy of subsequent evaluation data. Moreover, by determining the website type to which each judgment index extracted from the judgment file is respectively applicable, acquiring the judgment index corresponding to the website type of the target website according to the website type of the target website to obtain the judgment index set, the acquired judgment index set can be ensured to be adaptive to the target website, so that more accurate judgment indexes are provided for subsequent evaluation, and the accuracy of evaluation of website service capability is ensured.

In addition, on one hand, when the type of the evaluation index is an artificial type, the first preset interface receives the evaluation data corresponding to the manually input evaluation index, so that the problem that the evaluation data obtained by a machine is inaccurate can be avoided, and the accuracy of the subsequent evaluation result is improved. On the other hand, when the type of the evaluation index is a machine type, the machine crawler crawls the evaluation data corresponding to the assessment points of the evaluation index, so that the comprehensiveness of the acquired evaluation data is ensured, the accuracy of subsequent evaluation results is improved, manual operation is not needed, the labor cost is saved, and the evaluation efficiency is high. Furthermore, by receiving the sampling instruction from the second preset interface and outputting the judgment index corresponding to the sampling instruction and the judgment data corresponding to the judgment index according to the sampling instruction, a user can confirm the judgment data corresponding to different judgment indexes, the verification function of the judgment data corresponding to each judgment index is realized, and the accuracy of obtaining the judgment data of the judgment data during evaluation is further ensured. In addition, when a modification instruction issued by a user is received, the assessment point corresponding to the evaluation index is modified into an updated assessment point through the modification instruction, and assessment is performed again, so that the problem of inaccurate assessment result caused by deviation or abnormality of the assessment point can be avoided, and the accuracy is improved. And after the assessment points are updated, the keywords, the keyword groups and the combination relationship among the keywords are re-extracted in a machine self-learning mode, so that the determination of new assessment points can be realized according to the updated keywords, the updated keyword groups and the combination relationship among the keywords when the assessment indexes are assessed again subsequently, the obtained assessment data can be ensured to always correspond to the assessment indexes, and the accuracy of the assessment result of the website service capability is ensured.

The evaluation device for the website service capability comprises a processor and a memory, wherein the first acquisition unit, the second acquisition unit, the evaluation unit, the statistical unit and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.

The processor comprises a kernel, and the kernel calls the corresponding program unit from the memory. The kernel can be set to be one or more than one, and the accuracy of the evaluation result of the website service capability is improved by adjusting the kernel parameters.

The memory may include volatile memory in a computer readable medium, Random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip.

An embodiment of the present invention provides a storage medium on which a program is stored, the program implementing the method for evaluating web service capability when executed by a processor.

The embodiment of the invention provides a processor, which is used for running a program, wherein the evaluation method of the website service capability is executed when the program runs.

The embodiment of the invention provides equipment, which comprises a processor, a memory and a program which is stored on the memory and can run on the processor, wherein the processor executes the program and realizes the following steps: acquiring a judgment index tree corresponding to a target website, wherein a root node in the judgment index tree represents the website service capability, and each other node corresponds to a judgment index; acquiring evaluation data corresponding to each leaf evaluation index in an evaluation index tree from a target website, wherein the evaluation data are website contents corresponding to the evaluation points of the corresponding leaf evaluation indexes in the target website; judging the judgment data corresponding to each leaf judgment index according to the judgment rule corresponding to each leaf judgment index to obtain the judgment score corresponding to each leaf judgment index; and counting the evaluation scores of all leaf evaluation indexes of the target website to obtain the total score of the website service capability of the target website.

Further, before the obtaining of the judgment index tree corresponding to the target website, the method further includes:

extracting judgment indexes in the judgment files and the relation between the judgment indexes according to the judgment files; constructing a judgment index tree according to the judgment indexes and the relationship between the judgment indexes; and setting a judgment rule corresponding to the judgment index according to the judgment file, wherein the judgment rule comprises a judgment standard corresponding to the judgment index and scores corresponding to different degrees meeting the judgment standard.

Further, before the obtaining of the evaluation data corresponding to each leaf evaluation index in the evaluation index tree from the target website, the method further includes:

Further, the category of the evaluation index includes an artificial category and a machine category.

Further, the determining the check point corresponding to the leaf evaluation index according to the leaf evaluation index includes:

determining a key phrase corresponding to the leaf judgment index according to the leaf judgment index, wherein the key phrase comprises at least one keyword; determining a candidate point location group corresponding to the key phrase from a target website according to the key phrase, wherein the candidate point location group at least comprises one candidate point location; and determining the assessment point corresponding to the leaf evaluation index from the candidate point position grouping according to the matching degree of the key phrase and the website content of each candidate point position in the candidate point position grouping.

Further, if each judgment index has an applicable website type, the obtaining of the judgment index tree corresponding to the target website includes:

Further, after the judging data is judged according to the judging rule to obtain the judging score corresponding to the leaf judging index, the method further includes:

receiving a sampling instruction from a second preset interface, and outputting a leaf judgment index corresponding to the sampling instruction and judgment data corresponding to the leaf judgment index according to the sampling instruction; the counting of the evaluation scores of the leaf evaluation indexes of the target website to obtain the total score of the website service capability of the target website comprises the following steps: when a modification instruction is received, modifying the assessment point corresponding to the leaf assessment index into an updated assessment point according to the modification instruction, re-acquiring corresponding updated assessment data according to the updated assessment point, re-determining the assessment score, and counting the total score of the website service capability of the target website after the assessment point is updated.

The device in the embodiment of the invention can be a server, a PC, a PAD, a mobile phone and the like.

An embodiment of the present invention further provides a computer program product, which, when executed on a data processing apparatus, is adapted to execute a program that initializes the following method steps: acquiring a judgment index tree corresponding to a target website, wherein a root node in the judgment index tree represents the website service capability, and each other node corresponds to a judgment index; acquiring evaluation data corresponding to each leaf evaluation index in an evaluation index tree from a target website, wherein the evaluation data are website contents corresponding to the evaluation points of the corresponding leaf evaluation indexes in the target website; judging the judgment data corresponding to each leaf judgment index according to the judgment rule corresponding to each leaf judgment index to obtain the judgment score corresponding to each leaf judgment index; and counting the evaluation scores of all leaf evaluation indexes of the target website to obtain the total score of the website service capability of the target website.

Further, the category of the leaf judgment index includes an artificial category and a machine category.

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.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). The memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.

The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for evaluating service capability of a website is characterized by comprising the following steps:

2. The method according to claim 1, wherein before the obtaining of the judgment index tree corresponding to the target website, the method further comprises:

3. The method according to claim 2, wherein before the obtaining of the evaluation data corresponding to each leaf evaluation index in the evaluation index tree from the target website, the method further comprises:

4. The method of claim 3, wherein the categories of leaf judgment indicators comprise an artificial category and a machine category.

5. The method of claim 3, wherein determining, from the leaf evaluation indicator, a checkpoint corresponding to the leaf evaluation indicator comprises:

6. The method according to claim 2, wherein each criterion index has an applicable website type, and the obtaining the criterion index tree corresponding to the target website comprises:

7. The method according to any one of claims 1 to 6, wherein after the evaluating the evaluation data according to the evaluation rule to obtain the evaluation score corresponding to the leaf evaluation index, the method further comprises:

8. An apparatus for evaluating web site service capability, comprising:

9. A storage medium, characterized in that the storage medium comprises a stored program, wherein when the program runs, a device in which the storage medium is located is controlled to execute the method for evaluating website service capability according to any one of claims 1 to 7.

10. A processor for running a program, wherein the program runs the method for evaluating web site service capability according to any one of claims 1 to 7.