CN114201412B - Evaluation method for thousand-person and thousand-face degrees of search engine - Google Patents
Evaluation method for thousand-person and thousand-face degrees of search engine Download PDFInfo
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Abstract
The invention discloses a method and a system for evaluating the degree of thousands of people and thousands of faces of a search engine and a computer readable storage medium, wherein the method comprises the following steps: s1: defining a user group of a brand; s2: setting virtual users according to a defined user group, and designing a development plan according to the virtual users; s3: defining success indexes of virtual user formation and degree indexes of thousands of people and thousands of faces of a search engine; s4: utilizing the nurturing plan to nurture the virtual users, and selecting the nurtured virtual users according to success indexes of nurturing the virtual users; s5: and searching the keywords to be evaluated by using the established virtual users, and obtaining the thousand-person and thousand-face degrees of the search engine according to the search result. The invention can efficiently and intuitively test the thousand-person and thousand-face degree of the search engine by setting the virtual user and the creation plan, defining the index created by the virtual user and the thousand-person and thousand-face degree index and simultaneously combining the scatter diagram of the linear regression analysis.
Description
Technical Field
The invention relates to the technical field of big data, in particular to a method and a system for evaluating the thousand-person and thousand-face degrees of a search engine and a computer-readable storage medium.
Background
For any search platform, there are often differences in search results because user groups are different, and in order to verify that the thousand-face degree has a certain relevance with people, evaluation needs to be performed in search effects of different user groups to determine the thousand-face degree between different user groups according to an evaluation result.
In the prior art, evaluation on thousands of people and thousands of faces is generally realized by a mode of scoring a single content or counting the repetition degree in a search result, and the search result is scored manually, so that the operation efficiency is low, and the thousand-people and thousands of faces degree of the search result cannot be reflected more intuitively.
In the prior art, the publication numbers are: CN112287209A chinese invention patent discloses an intelligent recommendation method and system for thousand-person and thousand-face portals based on machine learning and collaborative filtering in 2021, month 29, the intelligent recommendation method includes: acquiring user data based on PKI/PMI information, authority information, access log and attention information of a user; performing data association degree analysis on the user data and platform resource data of thousands of people and thousands of portals based on an NLP algorithm model to obtain association degree information of the user data and the platform resource data; filtering and analyzing the association degree information of the user data and the platform resource data based on a collaborative filtering algorithm to obtain the association degree information after filtering and analyzing; and obtaining information to be recommended based on the relevance information after filtering and analyzing, sequencing the information to be recommended and recommending the information to a user. This prior art realizes thousand faces of people, but does not carry out the evaluation to the thousand faces degree of people of relevant system.
Disclosure of Invention
The invention provides a method and a system for evaluating the thousand-person and thousand-face degree of a search engine and a computer readable storage medium, aiming at overcoming the defects that the method for testing the thousand-person and thousand-face degree of the search engine or the platform in the prior art has low efficiency and cannot efficiently and intuitively evaluate.
The primary objective of the present invention is to solve the above technical problems, and the technical solution of the present invention is as follows:
the invention provides a method for evaluating the degree of thousands of people and thousands of faces of a search engine, which comprises the following steps:
s1: defining a user group of a brand;
s2: setting virtual users according to a defined user group, and designing a development plan according to the virtual users;
s3: defining a success index of virtual user formation and a degree index of thousands of people and thousands of faces of a search engine;
s4: utilizing the nurturing plan to nurture the virtual users, and selecting the nurtured virtual users according to success indexes of nurturing the virtual users;
s5: and searching the keywords to be evaluated by using the established virtual users, and obtaining the thousand-person and thousand-face degrees of the search engine according to the search result.
Further, the user group defining the brand is completed by registering in a search engine to set user social attributes and interest tags, wherein the user social attributes include: gender age, urban area; the interest tag comprises: skin care, animation, and movies.
Further, the setting of the virtual user is to set different user settings, and the creation plan includes: and selecting keywords related to the virtual user, and performing interactive operation on the search engine within a set time period.
Further, the success index of the virtual user is as follows: the ratio of the number of the content items related to the virtual user in the search engine home page is greater than or equal to a preset value.
Further, through setting up a plurality of test account number to every kind of virtual user and carrying out thousand people thousand face degree tests, thousand people thousand face degree index includes: the number of the retrieval results of the test accounts under the same virtual user after the same keyword is retrieved is not repeated, the number of the retrieval results of the test accounts under the same virtual user after the same keyword is retrieved is repeated, and the repetition rate of a single retrieval result.
Further, the repeated occurrences mean that a single search result appears 2 times or more.
Further, the degree of thousands of people can be subjected to regression analysis by constructing a scatter diagram, wherein the abscissa of the scatter diagram represents the proportion of the single search result a of the first virtual user A in the second personal device B, and the ordinate represents the proportion of the single search result a of the second virtual user B in the first personal device A.
The invention provides a system for evaluating the degree of thousands of people in a search engine, which comprises: the evaluation method comprises a memory and a processor, wherein the memory comprises a program of the evaluation method for the thousand-person and thousand-face degrees aiming at a search engine, and the program of the evaluation method for the thousand-person and thousand-face degrees aiming at the search engine realizes the following steps when being executed by the processor:
s1: defining a user group of a brand;
s2: setting virtual users according to a defined user group, and designing a cultivation plan according to the virtual users;
s3: defining success indexes of virtual user formation and degree indexes of thousands of people and thousands of faces of a search engine;
s4: utilizing the nurturing plan to nurture the virtual users, and selecting the nurtured virtual users according to success indexes of nurturing the virtual users;
s5: and searching the keywords to be evaluated by using the established virtual users, and obtaining the thousand-person and thousand-face degrees of the search engine according to the search result.
Further, the user group defining the brand is completed by registering in a search engine to set user social attributes and interest tags, wherein the user social attributes include: gender, age, urban area; the interest tag comprises: skin care, animation, and movies.
The third aspect of the invention discloses a computer-readable storage medium, wherein the computer-readable storage medium comprises a program of a thousand-person and thousand-face degree evaluation method for a search engine, and when the program of the thousand-person and thousand-face degree evaluation method for the search engine is executed by a processor, the steps of the thousand-person and thousand-face degree evaluation method for the search engine are realized.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
the invention can efficiently and intuitively test the thousand-person and thousand-face degree of the search engine by setting the virtual user and the creation plan, defining the index created by the virtual user and the thousand-person and thousand-face degree index and simultaneously combining the scatter diagram of the linear regression analysis.
Drawings
Fig. 1 is a flowchart of a method for evaluating the degree of thousands of people in a search engine according to an embodiment of the present invention.
FIG. 2 is a scatter diagram of two virtual user search results according to embodiments A and B of the present invention.
Fig. 3 is a diagram illustrating an effect of creating a virtual user for mom according to an embodiment of the present invention.
FIG. 4 is a diagram illustrating a virtual user creating an effect for a fashion girl in accordance with an embodiment of the present invention.
Fig. 5 is a schematic diagram illustrating a virtual user setting data acquisition for a mom in the embodiment of the present invention.
FIG. 6 is a schematic diagram of a virtual user acquiring data for a fashion girl device according to an embodiment of the invention.
Fig. 7 is a search result scatter diagram of a virtual user as mom and fashion girl according to the embodiment of the present invention.
Fig. 8 is a diagram showing pairwise comparison of three types of virtual user data according to the embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Example 1
As shown in fig. 1, a first aspect of the present invention provides a method for evaluating the degree of thousands of people in a search engine, comprising the following steps:
s1: defining a user group of a brand;
in a specific embodiment, a search engine to be evaluated and a corresponding user group are determined, and then the user group is specified by setting social attributes and interest tags during registration, where the social attributes may include: gender age, urban area, etc.; the interest tags may include: skin care, animation, movies, etc., and in one particular embodiment, the interest tag may also include: fashion putting on, nail art, color cosmetics, recipes, hairstyle, home furnishing, mother and infant, education, manual diy, emotion, body building, travel, painting, wedding, photography, TV drama, dance, laugh, lovely pet, star, lovely baby, music, stationery account, medical health, knowledge science popularization, personal care, reading, dining room, game, scientific and technological digital, automobile, comprehensive art, toy, script killer and the like.
S2: setting virtual users according to a defined user group, and designing a development plan according to the virtual users;
in a specific embodiment, virtual users, that is, virtual human devices, are set according to a defined user group, for example, a virtual user may set identities of "mom", "fashion girl", and the like, and set a formation plan of a corresponding virtual user, where the formation plan includes: the method includes the steps that keywords related to a virtual user are selected, interactive operation is conducted on a search engine within a set time period, for example, a virtual user can be subjected to one-month formation action, such as interaction of browsing, praise, collection, comment and the like on a search engine platform, when the virtual user is formed, a preset success index formed by the virtual user can be used for verification, degree evaluation can be conducted if the preset success index is met, and therefore it is guaranteed that the behaviors of browsing, praise and the like do not affect a search result.
S3: defining success indexes of virtual user formation and degree indexes of thousands of people and thousands of faces of a search engine;
in one embodiment, the success indicators of virtual user fostering are: the content number ratio of the search engine home page to the virtual user is greater than or equal to a preset value, for example, the content number ratio of the search engine home page to the virtual user is greater than or equal to 60%; carry out thousand people thousand faces degree test through setting up a plurality of test account number to every kind of virtual user, thousand people thousand faces degree index includes: the number of the search results of the same virtual user after the same keyword is searched by a plurality of test accounts is not repeated, the number of the search results of the same virtual user after the same keyword is searched by a plurality of test accounts is repeated, and the repetition rate of a single search result is increased. For example, a plurality of different types of virtual users may be set, for example, three types of virtual users may be set, each virtual user sets 10 account numbers, searches for keywords through 10 account numbers, and respectively counts the number of unrepeated search results after the same keyword is searched by the next 10 test account numbers of the same virtual user, the number of repeated search results after the same keyword is searched by the next 10 test account numbers of the same virtual user, and the repetition rate of a single search result;
s4: utilizing the nurturing plan to nurture the virtual users, and selecting the nurtured virtual users according to success indexes of nurturing the virtual users;
s5: and searching the keywords to be evaluated by using the established virtual users, and obtaining the thousand-person and thousand-face degrees of the search engine according to the search result.
In a specific embodiment, for example, the same keyword search is performed on 10 test accounts of the same virtual user, a. the number of posts that do not appear repeatedly is 7, that is, 10 people have 7 posts, and the ranking non-repetition rate is (7/10) × 100% = 70%;
b. the number of repeatedly appearing notes is 2 (the definition of "repeatedly appearing" is the number of notes that appear 2 times or more);
c. the single search result repetition rate was calculated as (1-70%)/2 = 15%;
it should be noted that the lower the average repetition of the single content, the higher the level of thousands of people in the position.
In addition, the degree of thousands of people can be subjected to regression analysis by constructing a scatter diagram, wherein the abscissa of the scatter diagram represents the proportion of the single search result a of the first virtual user A appearing in the second personal device B, and the ordinate represents the proportion of the single search result a of the second virtual user B appearing in the first personal device A. As shown in fig. 2, two scattergrams of virtual users a and B have a linear regression equation: y = 0.3691x + 0.1891, and R2 = 0.1556, the lower the y value, the higher the thousand faces, the more dispersed the distribution of the graph is as can be seen from fig. 2, and the distribution graph can more intuitively illustrate that the degree of the thousand faces is higher compared with the data statistics.
Example 2
The invention provides a system for evaluating the degree of thousands of people in a search engine, which comprises: the evaluation method comprises a memory and a processor, wherein the memory comprises a program of the evaluation method for the thousand-person and thousand-face degrees aiming at a search engine, and when the program of the evaluation method for the thousand-person and thousand-face degrees aiming at the search engine is executed by the processor, the following steps are realized:
s1: defining a user group of a brand;
in a specific embodiment, a search engine to be evaluated and a corresponding user group are determined, and then the user group is specified by setting social attributes and interest tags during registration, where the social attributes may include: gender age, urban area, etc.; the interest tags may include: skin care, animation, movies, etc., and in one particular embodiment, the interest tag may also include: fashion putting on, nail art, color cosmetics, recipes, hairstyle, home furnishing, mother and infant, education, manual diy, emotion, body building, travel, painting, wedding, photography, TV drama, dance, laugh, lovely pet, star, lovely baby, music, stationery account, medical health, knowledge science popularization, personal care, reading, dining room, game, scientific and technological digital, automobile, comprehensive art, toy, script killer and the like.
S2: setting virtual users according to a defined user group, and designing a development plan according to the virtual users;
in a specific embodiment, a virtual user is set according to a defined user group, the virtual user is a virtual human device, for example, the virtual user may set identities of "mom", "fashion girl", and the like, and set a fostering plan of the corresponding virtual user, where the fostering plan includes: the method includes the steps that keywords related to a virtual user are selected, interactive operation is conducted on a search engine within a set time period, for example, a virtual user can be subjected to one-month formation action, such as interaction of browsing, praise, collection, comment and the like on a search engine platform, when the virtual user is formed, a preset success index of formation of the virtual user can be used for verification, degree evaluation can be conducted if the preset success index is met, and therefore it is guaranteed that the behaviors of browsing, praise and the like do not affect a search result.
S3: defining success indexes of virtual user formation and degree indexes of thousands of people and thousands of faces of a search engine;
in one embodiment, the success indicators of virtual user fostering are: the content number ratio of the search engine home page to the virtual user is greater than or equal to a preset value, for example, the content number ratio of the search engine home page to the virtual user is greater than or equal to 60%; carry out thousand people thousand faces degree test through setting up a plurality of test account number to every kind of virtual user, thousand people thousand faces degree index includes: the number of the search results of the same virtual user after the same keyword is searched by a plurality of test accounts is not repeated, the number of the search results of the same virtual user after the same keyword is searched by a plurality of test accounts is repeated, and the repetition rate of a single search result is increased. For example, a plurality of different types of virtual users may be set, for example, three types of virtual users may be set, each virtual user sets 10 account numbers, searches for keywords through 10 account numbers, and respectively counts the number of unrepeated search results after the same keyword is searched by the next 10 test account numbers of the same virtual user, the number of repeated search results after the same keyword is searched by the next 10 test account numbers of the same virtual user, and the repetition rate of a single search result;
s4: utilizing the nurturing plan to nurture the virtual users, and selecting the nurtured virtual users according to success indexes of nurturing the virtual users;
s5: searching the keywords to be evaluated by using the developed virtual users, and obtaining the thousands of people and thousands of faces of the search engine according to the search result.
In a specific embodiment, for example, the same keyword search is performed on 10 test accounts of the same virtual user, a. the number of posts that do not appear repeatedly is 7, that is, 10 people have 7 posts, and the ranking non-repetition rate is (7/10) × 100% = 70%;
b. the number of repeatedly appearing notes is 2 (the definition of "repeatedly appearing" is the number of notes that appear 2 times or more);
c. the single search result repetition rate was calculated as (1-70%)/2 = 15%;
it should be noted that the lower the average repetition of the single content, the higher the level of thousands of people in the position.
In addition, the degree of thousands of people can be subjected to regression analysis by constructing a scatter diagram, wherein the abscissa of the scatter diagram represents the proportion of the single search result a of the first virtual user A appearing in the second personal device B, and the ordinate represents the proportion of the single search result a of the second virtual user B appearing in the first personal device A. As shown in fig. 2, two scattergrams of virtual users a and B have a linear regression equation: y = 0.3691x + 0.1891, and R2 = 0.1556, the lower the y value, the higher the thousand faces, the more dispersed the distribution of the graph is as can be seen from fig. 2, and the distribution graph can more intuitively illustrate that the degree of the thousand faces is higher compared with the data statistics.
The third aspect of the invention discloses a computer-readable storage medium, wherein the computer-readable storage medium comprises a program of a thousand-person and thousand-face degree evaluation method for a search engine, and when the program of the thousand-person and thousand-face degree evaluation method for the search engine is executed by a processor, the steps of the thousand-person and thousand-face degree evaluation method for the search engine are realized.
Example 3
Based on the method, the embodiment specifically sets two virtual users (human devices) to perform result verification analysis.
(A) 2 groups of people are selected, each group of people is provided with 10 users, A group of people is provided with a mother, and B group of fashionable girls is used as comparison
a1. Performing a cultivation action for 1 month on each group of people, browsing 5 keywords at different time intervals every day, and performing artificial interaction on the search results to ensure the cultivation of people;
a2. after 1 month of fostering, according to 60% of the recommended page note of the home page + the content which accords with the design of the person, the fostering is regarded as successful fostering, fig. 3 shows the fostering effect of the mom, and fig. 4 shows the fostering effect of the fashion girl.
a3. After successful fostering, keywords such as whitening essence are searched for, TOP40 data are searched for and obtained, fig. 5 shows that mom sets for obtaining data, and fig. 6 shows that fashion girls sets for obtaining data.
a4. A scatter diagram is obtained through statistics of a linear regression equation Y = AX + B, and the scatter distribution diagram of FIG. 7 shows that the thousand-person and thousand-face degrees of AB are high.
B. Based on the above test groups A and B, a group C of 'maiden in love' is added, search statistics is carried out after same cultivation, fig. 8 is a data pairwise comparison graph set by A, B, C three persons, it can be seen from fig. 8 that the thousand-face degree of the group A and the B, C are higher, the thousand-face degree of the group B, C is lower, and meanwhile, as can be seen from fig. 7, under the condition that the persons are set to be similar (such as the person BC), the thousand-face degree of the two search results is lower, and under the condition that the human setting is large in similarity difference (such as the person AB and the person AC), the thousand-face degree of the two search results is larger.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (8)
1. A method for evaluating the degree of thousands of people and thousands of faces of a search engine is characterized by comprising the following steps:
s1: defining a user group of a brand;
s2: setting virtual users according to a defined user group, and designing a development plan according to the virtual users; the setting of the virtual user is to set different user settings, and the creation plan includes: selecting keywords related to the virtual user, and performing interactive operation on a search engine within a set time period;
s3: defining success indexes of virtual user formation and degree indexes of thousands of people and thousands of faces of a search engine;
s4: utilizing the nurturing plan to nurture the virtual users, and selecting the nurtured virtual users according to success indexes of nurturing the virtual users;
s5: searching keywords to be evaluated by using the established virtual users, and obtaining the thousand-person and thousand-face degrees of the search engine according to the search result; through setting up a plurality of test account number to every kind of virtual user and carrying out thousand people thousand face degree tests, thousand people thousand face degree index include: the number of the search results of the same virtual user after the same keyword is searched by a plurality of test accounts is not repeated, the number of the search results of the same virtual user after the same keyword is searched by a plurality of test accounts is repeated, and the repetition rate of a single search result is increased.
2. The method for evaluating the degree of thousands of people in a search engine according to claim 1, wherein the user group defining the brand is completed by registering in the search engine to set user social attributes and interest tags, wherein the user social attributes comprise: gender age, urban area; the interest tag comprises: skin care, animation, and movies.
3. The method for evaluating the degree of thousands of people in a search engine according to claim 1, wherein the success indicators of the virtual user's cultivation are as follows: the ratio of the number of the content items related to the virtual user in the search engine home page is greater than or equal to a preset value.
4. The method as claimed in claim 1, wherein the repeated occurrences of a single search result are 2 or more times.
5. The method as claimed in claim 1, wherein the evaluation method for the thousand-person/thousand-face degree of the search engine further comprises constructing a scatter diagram to perform regression analysis, wherein the abscissa of the scatter diagram represents the proportion of the first type of virtual user A single search result a appearing in the second type of personal device B, and the ordinate represents the proportion of the second type of virtual user B single search result a appearing in the first type of personal device A.
6. A system for evaluating the degree of thousands of people in a search engine, comprising: the evaluation method comprises a memory and a processor, wherein the memory comprises a program of the evaluation method for the thousand-person and thousand-face degrees aiming at a search engine, and when the program of the evaluation method for the thousand-person and thousand-face degrees aiming at the search engine is executed by the processor, the following steps are realized:
s1: defining a user group of a brand;
s2: setting virtual users according to a defined user group, and designing a development plan according to the virtual users;
the setting of the virtual user is to set different user settings, and the creation plan includes: selecting keywords related to the virtual user, and performing interactive operation on a search engine within a set time period;
s3: defining success indexes of virtual user formation and degree indexes of thousands of people and thousands of faces of a search engine;
s4: utilizing the nurturing plan to nurture the virtual users, and selecting the nurtured virtual users according to success indexes of nurturing the virtual users;
s5: searching keywords to be evaluated by using the established virtual users, and obtaining the thousand-person and thousand-face degrees of the search engine according to the search result;
carry out thousand people thousand faces degree test through setting up a plurality of test account number to every kind of virtual user, thousand people thousand faces degree index includes: the number of the retrieval results of the test accounts under the same virtual user after the same keyword is retrieved is not repeated, the number of the retrieval results of the test accounts under the same virtual user after the same keyword is retrieved is repeated, and the repetition rate of a single retrieval result.
7. The system for evaluating the degree of thousands of people in a search engine according to claim 6, wherein the group of users defining the brand is completed by registering in the search engine to set user social attributes and interest tags, wherein the user social attributes comprise: gender age, urban area; the interest tag comprises: skin care, animation, and movies.
8. A computer-readable storage medium, wherein the computer-readable storage medium includes a program for a thousand-person/thousand-face degree evaluation method for a search engine, and when the program for the thousand-person/thousand-face degree evaluation method for the search engine is executed by a processor, the steps of the method for the thousand-person/thousand-face degree evaluation for the search engine according to any one of claims 1 to 7 are implemented.
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