CN108804676B - Post sorting method, device and equipment and computer readable storage medium - Google Patents
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Abstract
The invention discloses a post sorting method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: calculating the score value of each post under each detail page behavior index according to the behavior data of the user in each detail page of each post; calculating the ranking of each post under the behavior index of the detail page according to the score value of all posts under the behavior index of the detail page; determining the lowest ranking of each post under all the detail page behavior indexes according to the ranking of each post under each detail page behavior index; and sorting all the posts according to the determined lowest rank of each post. The method and the device can eliminate posts with poor quality in ranking and improve the experience degree of the user.
Description
Technical Field
The present invention relates to the field of internet technologies, and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for sorting posts.
Background
With the continuous development of internet technology, data information in the internet is increasingly huge, and users often need to perform search operation to acquire desired information. In the prior art, the posts in the search result are usually sorted by using a single sort index, such as: the posts are sorted by time of posting or by click rate of the posts. However, the sorting mode in the prior art has the problems of single sorting index and poor sorting effect; there is also a phenomenon that posts with poor quality appear in the ranking, thereby affecting the user experience.
Disclosure of Invention
The embodiment of the invention mainly aims to provide a post sorting method, a device, equipment and a computer readable storage medium, which can eliminate posts with poor quality in ranking and improve the experience of a user.
In order to achieve the above object, an embodiment of the present invention provides a post ranking method, where the method includes:
calculating the score value of each post under each detail page behavior index according to the behavior data of the user in each detail page of each post;
calculating the ranking of each post under the behavior index of the detail page according to the score value of all posts under the behavior index of the detail page;
determining the lowest ranking of each post under all the detail page behavior indexes according to the ranking of each post under each detail page behavior index;
and sorting all the posts according to the determined lowest rank of each post.
Optionally, before the calculating the rank of each post under a detail page behavior index according to the score value of all posts under the detail page behavior index, the method further includes:
and merging the detail page behavior indexes of the same type of each post, and calculating the score value of the merged detail page behavior indexes of each post according to a preset algorithm.
Optionally, after sorting all posts according to the determined lowest rank of each post, the method further includes:
screening out n posts according to a sorting result and a preset screening rule, and displaying the n posts in a list page; wherein n is a positive integer.
Optionally, after sorting all posts according to the determined lowest rank of each post, the method further includes:
screening n posts according to a preset screening rule according to the sorting result, and calculating the sum of the score values of all detail page behavior indexes of each screened post;
calculating a score value of a list page behavior index of each post after being screened according to the behavior data of each post after being screened in the list page by the user;
and sorting all the screened posts according to the product value of the score value of the list page behavior index of each screened post and the corresponding sum value, and displaying the sorting result in a list page.
Optionally, the detail page behavior index includes at least one of: the system comprises a telephone conversion rate, a short message conversion rate, a micro chat conversion rate, collection times, forwarding times and page retention time.
Optionally, the list page behavior index includes: click through rate.
In addition, to achieve the above object, an embodiment of the present invention further provides a post sorting apparatus, including:
the calculation module is used for calculating the score value of each post under each detail page behavior index according to the behavior data of the user in each detail page of each post;
the first ranking module is used for calculating the ranking of each post under the detail page behavior index according to the score value of all posts under the detail page behavior index;
the determining module is used for determining the lowest ranking of each post under all the detail page behavior indexes according to the ranking of each post under each detail page behavior index;
and the second sorting module is used for sorting all the posts according to the determined lowest rank of each post.
Optionally, the apparatus further comprises:
the display module is used for screening out n posts according to the sorting result and a preset screening rule and displaying the n posts in a list page; wherein n is a positive integer.
In addition, to achieve the above object, an embodiment of the present invention further provides a post sorting apparatus, where the apparatus includes: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is used for executing the post sorting program stored in the memory so as to realize the steps of the introduced post sorting method.
In addition, to achieve the above object, an embodiment of the present invention further provides a computer-readable storage medium, where a post ranking program is stored;
when executed by at least one processor, cause the at least one processor to perform the steps of the post ranking method described above.
The method, the device, the equipment and the computer-readable storage medium for sorting the posts, which are provided by the embodiment of the invention, introduce various sorting indexes, sort all the posts according to the score values of all the posts under a single index, and obtain the ranking of all the posts under the single index. And then determining the lowest ranking of the posts under a plurality of indexes, namely the most lagging ranking, and sequencing all the posts based on the lowest ranking of each post. Therefore, posts with poor quality in ranking are eliminated, only posts with high comprehensive scores in all ranking indexes are shown to the user, and browsing experience of the user is improved.
Drawings
FIG. 1 is a flow diagram of a post ranking method of a first embodiment of the present invention;
FIG. 2 is a flow chart of a post ranking method of a second embodiment of the present invention;
FIG. 3 is a flow chart of a post ranking method of a third embodiment of the present invention;
FIG. 4 is a flow chart of a post ranking method of a fourth embodiment of the present invention;
FIG. 5 is a diagram illustrating the structure of a post sorting device according to a fifth embodiment of the present invention;
fig. 6 is a schematic diagram showing the composition structure of a post ranking apparatus according to a sixth embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the embodiments of the present invention for achieving the intended purpose, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments.
A first embodiment of the present invention provides a method for sorting posts, as shown in fig. 1, the method specifically includes the following steps:
step S101: and calculating the score value of each post under each detail page behavior index according to the behavior data of the user in the detail page of each post.
In the embodiment of the invention, the post is a record in a list page, and the list page comprises a plurality of posts; the detail page is the page entered after clicking on the post in the list page. For example, a search result page after searching on a search website is a list page, each search result presented in the list page is a post, and a page entered after clicking on a post is a detail page of the post.
Specifically, step S101 includes:
step A1: and counting the behavior data of a plurality of users in the detail page of each post in a set time period.
Wherein the behavior data of the user in the detail page of each post comprises: click behavior data, browsing time data, and input text data.
Step A2: and calculating the score value of each post under each preset detail page behavior index according to the statistical result and a preset algorithm.
Further, step S101 further includes: normalizing the score value of each detail page behavior index to a certain numerical value range according to the following formula:
wherein, Score is a Score value calculated according to a preset algorithm;
mu is the average score value of all posts under any detail page behavior index;
sigma is the standard deviation of all posts under any detail page behavior index;
Step S102: and calculating the ranking of each post under the detailed page behavior index according to the score value of all posts under the detailed page behavior index.
In the embodiment of the invention, the ranking of a post under each detail page behavior index is obtained according to the mode of the step S102. For example, the ranking of a post under each detail page behavior index is: 58. 12, 36, 41, 18.
Step S103: and determining the lowest ranking of each post under the behavior indexes of all the detail pages according to the ranking of each post under the behavior indexes of all the detail pages.
The lowest ranking is the most lagging ranking, but is numerically the largest ranking. For example, if the ranking of a post under each detail page behavior index is: 58. 12, 36, 41, 18, the lowest rank name of the post is 58.
Step S104: and sorting all the posts according to the determined lowest rank of each post.
Specifically, in the embodiment of the invention, all posts are sorted in an ascending order according to the lowest ranking of each post under each detail page behavior index, so that the prior posts cannot appear in the condition of extremely low ranking under a certain detail page behavior index, and the comprehensive quality of the prior posts is ensured to be high.
Specifically, after step S104, the method further includes:
screening out n posts according to a sorting result and a preset screening rule, and displaying the n posts in a list page; wherein n is a positive integer.
Further, if all posts are sorted in ascending order in step S104, a preset screening rule is set to screen out the top n posts; if all posts are sorted in descending order in step S104, the preset screening rule is to screen out the next n posts.
Compared with the prior art, in the embodiment of the invention, the score value of each post under a plurality of ranking indexes is calculated according to the behavior data of the user in the detail page of the post. And sorting all the posts according to the point values of all the posts under the single sorting index to obtain the ranking of all the posts under the single sorting index. And then determining the lowest ranking of one post under a plurality of ranking indexes, namely the most lagging ranking, performing ascending ranking according to the lowest ranking of the posts, and displaying the posts ranked in the front in a list page. Therefore, the posts displayed in the list page are guaranteed to be high-quality posts, poor-quality posts cannot exist, and the browsing experience of the user is improved.
A second embodiment of the present invention provides a method for sorting posts, as shown in fig. 2, the method specifically includes the following steps:
step S201: and calculating the score value of each post under each detail page behavior index according to the behavior data of the user in the detail page of each post.
In the embodiment of the invention, the post is a record in a list page, and the list page comprises a plurality of posts; the detail page is the page entered after clicking on the post in the list page. For example, a search result page after searching on a search website is a list page, each search result presented in the list page is a post, and a page entered after clicking on a post is a detail page of the post.
Specifically, step S201 includes:
step A1: and counting the behavior data of a plurality of users in the detail page of each post in a set time period.
Wherein the behavior data of the user in the detail page of each post comprises: click behavior data, browsing time data, and input text data.
Step A2: and calculating the score value of each post under each preset detail page behavior index according to the statistical result and a preset algorithm.
Further, step S201 further includes: normalizing the score value of each detail page behavior index to a certain numerical value range according to the following formula:
wherein, Score is a Score value calculated according to a preset algorithm;
mu is the average score value of all posts under any detail page behavior index;
sigma is the standard deviation of all posts under any detail page behavior index;
Step S202: and calculating the ranking of each post under the detailed page behavior index according to the score value of all posts under the detailed page behavior index.
In the embodiment of the invention, the ranking of a post under each detail page behavior index is obtained according to the mode of the step S202. For example, the ranking of a post under each detail page behavior index is: 58. 12, 36, 41, 18.
Step S203: and determining the lowest ranking of each post under the behavior indexes of all the detail pages according to the ranking of each post under the behavior indexes of all the detail pages.
The lowest ranking is the most lagging ranking, but is numerically the largest ranking. For example, if the ranking of a post under each detail page behavior index is: 58. 12, 36, 41, 18, the lowest rank name of the post is 58.
Step S204: and sorting all the posts according to the determined lowest rank of each post.
Step S205: and screening n posts according to a preset screening rule according to the sorting result, and calculating the sum of the score values of all detail page behavior indexes of each screened post.
Specifically, if all posts are sorted in ascending order in step S204, the preset screening rule is to screen out the top n posts; if all posts are sorted in descending order in step S204, the preset screening rule is to screen out the next n posts.
Step S206: and calculating the score value of the list page behavior index of each post after screening according to the behavior data of each post after screening in the list page by the user.
Specifically, the behavior data of the user for each post in the list page includes: click behavior data;
the list page behavior indicators include: click through rate.
Step S207: and sorting all the screened posts according to the product value of the score value of the list page behavior index of each screened post and the corresponding sum value, and displaying the sorting result in a list page.
Preferably, all posts after the filtering are sorted in descending order in step S207.
In the embodiment of the invention, the posts are sorted twice, and the primary sorting is carried out according to the lowest ranking of each post under each detail page behavior index, so that part of posts with better quality are screened out from numerous posts; and performing secondary sorting according to the list page behavior index and the detail page behavior index of each screened post, thereby ensuring that the posts ranked in the front do not have poor quality.
A third embodiment of the present invention provides a method for sorting posts, as shown in fig. 3, the method specifically includes the following steps:
step S301: and calculating the score value of each post under each detail page behavior index according to the behavior data of the user in the detail page of each post.
In the embodiment of the invention, the post is a record in a list page, and the list page comprises a plurality of posts; the detail page is the page entered after clicking on the post in the list page. For example, a search result page after searching on a search website is a list page, each search result presented in the list page is a post, and a page entered after clicking on a post is a detail page of the post.
Specifically, step S301 includes:
step A1: and counting the behavior data of a plurality of users in the detail page of each post in a set time period.
Wherein the behavior data of the user in the detail page of each post comprises: click behavior data, browsing time data, and input text data.
Step A2: and calculating the score value of each post under each preset detail page behavior index according to the statistical result and a preset algorithm.
Further, step S301 further includes: normalizing the score value of each detail page behavior index to a certain numerical value range according to the following formula:
wherein, Score is a Score value calculated according to a preset algorithm;
mu is the average score value of all posts under any detail page behavior index;
sigma is the standard deviation of all posts under any detail page behavior index;
Further, the detail page behavior index includes: the system comprises a telephone conversion rate, a short message conversion rate, a micro chat conversion rate, collection times, forwarding times and page retention time.
Wherein the telephone conversion rate is the frequency of the contact between the user and the merchant through the telephone information in the detail page; the short message conversion rate is the frequency of the contact between the user and the merchant through the short message service set in the detail page; chat conversion is the frequency with which a user contacts a merchant through instant messaging service provided in a details page.
As shown in Table 1, for the calculated score values for posts numbered 001 through 350 at each detail page behavior index:
TABLE 1
Step S302: and merging the detail page behavior indexes of the same type of each post, and calculating the score value of the merged detail page behavior indexes of each post according to a preset algorithm.
Preferably, the preset algorithm is an arithmetic mean algorithm.
For example, the phone conversion rate, the short message conversion rate and the chat conversion rate in table 1 are the same type of detail page behavior indexes, and may be combined into a communication conversion rate, and the score value of each post after combination under each detail page behavior index is shown in table 2:
TABLE 2
Step S303: and calculating the ranking of each post under the detailed page behavior index according to the score value of all posts under the detailed page behavior index.
As shown in Table 3, the ranking of all posts under each detail page behavior index is:
TABLE 3
Step S304: and determining the lowest ranking of each post under the behavior indexes of all the detail pages according to the ranking of each post under the behavior indexes of all the detail pages.
For example, as shown in table 4, the lowest row names numbered 001 to 350 are:
TABLE 4
Step S305: and sorting all the posts in an ascending order according to the determined lowest rank of each post.
For example, according to the lowest ranking of the individual posts as shown in table 4, the ascending sort result is: #349, #350, #003, #001, #004, and # 002.
It should be noted that if the lowest ranking of the posts is the same, for example: the lowest rank of the post #001 and the post #004 is 5, and the post #001 and the post #004 are arranged in parallel in the ascending sorting result, and the sequence is randomly set.
Step S306: according to the ascending sorting result, displaying the first n posts in a list page; wherein n is a positive integer.
A fourth embodiment of the present invention provides a post ranking method, as shown in fig. 4, the method specifically includes the following steps:
step S401: and calculating the score value of each post under each detail page behavior index according to the behavior data of the user in the detail page of each post.
In the embodiment of the invention, the post is a record in a list page, and the list page comprises a plurality of posts; the detail page is the page entered after clicking on the post in the list page. For example, a search result page after searching on a search website is a list page, each search result presented in the list page is a post, and a page entered after clicking on a post is a detail page of the post.
Specifically, step S401 includes:
step A1: and counting the behavior data of a plurality of users in the detail page of each post in a set time period.
Wherein the behavior data of the user in the detail page of each post comprises: click behavior data, browsing time data, and input text data.
Step A2: and calculating the score value of each post under each preset detail page behavior index according to the statistical result and a preset algorithm.
Further, step S401 further includes: normalizing the score value of each detail page behavior index to a certain numerical value range according to the following formula:
wherein, Score is a Score value calculated according to a preset algorithm;
mu is the average score value of all posts under any detail page behavior index;
sigma is the standard deviation of all posts under any detail page behavior index;
Further, in the embodiment of the present invention, the detail page behavior index includes: the system comprises a telephone conversion rate, a short message conversion rate, a micro chat conversion rate, collection times, forwarding times and page retention time.
Wherein the telephone conversion rate is the frequency of the contact between the user and the merchant through the telephone information in the detail page; the short message conversion rate is the frequency of the contact between the user and the merchant through the short message service set in the detail page; chat conversion is the frequency with which a user contacts a merchant through instant messaging service provided in a details page.
As shown in Table 5, for the calculated score values for posts numbered 001 through 350 at each detail page behavior index:
TABLE 5
Step S402: and merging the detail page behavior indexes of the same type of each post, and calculating the score value of the merged detail page behavior indexes of each post according to a preset algorithm.
Preferably, the preset algorithm is an arithmetic mean algorithm.
For example, the phone conversion rate, the short message conversion rate and the chat conversion rate in table 5 are the same type of detail page behavior indexes, and may be combined into a communication conversion rate, and the score value of each post after combination under each detail page behavior index is shown in table 6:
TABLE 6
Step S403: a score value of a list page behavior index for each post is calculated based on the user's behavior data for each post in the list page.
Specifically, the behavior data of the user for each post in the list page includes: click behavior data;
the list page behavior indicators include: click through rate.
As shown in Table 7, for the score value of the click rate of each post:
TABLE 7
Step S404: and obtaining the ranking of each post under the detailed page behavior index according to the point value of all posts under the detailed page behavior index.
For example, as shown in Table 8, for all posts, the ranking under each detail page behavior index:
TABLE 8
Step S405: and determining the lowest ranking of each post under the behavior indexes of all the detail pages according to the ranking of each post under the behavior indexes of all the detail pages.
For example, as shown in table 9, the lowest row names numbered 001 to 350 are:
TABLE 9
Step S406: and sorting all posts in an ascending order according to the determined lowest rank of each post, and screening the top n posts according to the ascending order sorting result.
Step S407: and calculating the total value of the point values of all detail page behavior indexes of each post after screening.
As shown in Table 10, for the sum of the top n posts:
watch 10
Step S408: and sorting all the screened posts in a descending order according to the product value of the score value of the list page behavior index of each screened post and the corresponding sum value, and displaying the sorting result in a list page.
As shown in table 11, the product value of the sum value and the click rate of the top n posts, and the comprehensive ranking according to the product value:
TABLE 11
A fifth embodiment of the present invention provides a method for sorting posts, as shown in fig. 5, where the apparatus specifically includes the following components:
a calculating module 501, configured to calculate a score value of each post under each detail page behavior index according to behavior data of a user in each detail page of each post;
a first ranking module 502, configured to calculate, according to the score values of all the posts under a detail page behavior index, a ranking of each post under the detail page behavior index;
a determining module 503, configured to determine, according to the ranking of each post under each detail page behavior index, a lowest ranking of each post under all detail page behavior indexes;
a second ranking module 504, configured to rank all the posts according to the determined lowest rank of each post.
Specifically, the apparatus further comprises:
and the merging module is used for merging the detail page behavior indexes of the same type of each post before the ranking of each post under the detail page behavior indexes is obtained by calculation according to the score values of all posts under one detail page behavior index, and calculating the score value of the detail page behavior index after each post is merged according to a preset algorithm.
Further, the apparatus further comprises:
the display module is used for screening out n posts according to the sorting result and a preset screening rule and displaying the n posts in a list page; wherein n is a positive integer.
Further, the apparatus further comprises:
the processing module is used for screening n posts according to the sorting result and a preset screening rule and calculating the sum of the score values of all detail page behavior indexes of each screened post; calculating a score value of a list page behavior index of each post after being screened according to the behavior data of each post after being screened in the list page by the user; and sorting all the screened posts according to the product value of the score value of the list page behavior index of each screened post and the corresponding sum value, and displaying the sorting result in a list page.
Further, the detail page behavior index includes at least one of: the system comprises a telephone conversion rate, a short message conversion rate, a micro chat conversion rate, collection times, forwarding times and page retention time.
The list page behavior indicators include: click through rate.
A sixth embodiment of the present invention provides a post ranking apparatus, as shown in fig. 6, the apparatus comprising: a processor 601, a memory 602, and a communication bus;
the communication bus is used for realizing connection communication between the processor 601 and the memory 602;
processor 601 is configured to execute the post ranking program stored in memory 602 to implement the following steps:
calculating the score value of each post under each detail page behavior index according to the behavior data of the user in each detail page of each post;
calculating the ranking of each post under the behavior index of the detail page according to the score value of all posts under the behavior index of the detail page;
determining the lowest ranking of each post under all the detail page behavior indexes according to the ranking of each post under each detail page behavior index;
and sorting all the posts according to the determined lowest rank of each post.
A seventh embodiment of the present invention proposes a computer-readable storage medium storing a post ranking program;
when executed by at least one processor, the post ranking program causes the at least one processor to perform the steps of:
calculating the score value of each post under each detail page behavior index according to the behavior data of the user in each detail page of each post;
calculating the ranking of each post under the behavior index of the detail page according to the score value of all posts under the behavior index of the detail page;
determining the lowest ranking of each post under all the detail page behavior indexes according to the ranking of each post under each detail page behavior index;
and sorting all the posts according to the determined lowest rank of each post.
The method, the device, the equipment and the computer-readable storage medium for sorting the posts introduce various sorting indexes, sort all the posts according to the score values of all the posts under a single index, and obtain the ranks of all the posts under the single index. And then determining the lowest ranking of the posts under a plurality of indexes, namely the most lagging ranking, and sequencing all the posts based on the lowest ranking of each post. Therefore, posts with poor quality in ranking are eliminated, only posts with high comprehensive scores in all ranking indexes are shown to the user, and browsing experience of the user is improved.
While the embodiments of the present invention have been described in terms of specific embodiments, it is to be understood that both the foregoing general description and the following detailed description are intended to provide further explanation and understanding of the invention as claimed.
Claims (10)
1. A method of ranking posts, the method comprising:
calculating the score value of each post under each detail page behavior index according to the behavior data of the user in each detail page of each post;
calculating the ranking of each post under the behavior index of the detail page according to the score value of all posts under the behavior index of the detail page;
determining the lowest ranking of each post under all the detail page behavior indexes according to the ranking of each post under each detail page behavior index;
sorting all posts according to the determined lowest rank of each post;
the calculating the score value of each post under each detail page behavior index according to the behavior data of the user in the detail page of each post comprises:
counting the behavior data of a plurality of users in the detail page of each post in a set time period, wherein the behavior data of the users in the detail page of each post comprises the following steps: click behavior data, browsing time data and input text data;
and calculating the score value of each post under each preset detail page behavior index according to the statistical result and a preset algorithm, and normalizing the score value of each detail page behavior.
2. The method of claim 1, wherein prior to said calculating a ranking of each post under a detail page behavior index based on the score values of all posts under said detail page behavior index, the method further comprises:
and merging the detail page behavior indexes of the same type of each post, and calculating the score value of the merged detail page behavior indexes of each post according to a preset algorithm.
3. The method of claim 1, wherein after said sorting all posts according to the determined lowest ranking of each post, the method further comprises:
screening out n posts according to a sorting result and a preset screening rule, and displaying the n posts in a list page; wherein n is a positive integer.
4. The method of claim 1, wherein after said sorting all posts according to the determined lowest ranking of each post, the method further comprises:
screening n posts according to a preset screening rule according to the sorting result, and calculating the sum of the score values of all detail page behavior indexes of each screened post;
calculating a score value of a list page behavior index of each post after being screened according to the behavior data of each post after being screened in the list page by the user;
and sorting all the screened posts according to the product value of the score value of the list page behavior index of each screened post and the corresponding sum value, and displaying the sorting result in a list page.
5. The method of claim 1, wherein the detail page behavior indicators comprise at least one of: the system comprises a telephone conversion rate, a short message conversion rate, a micro chat conversion rate, collection times, forwarding times and page retention time.
6. The method of claim 4, wherein the list page behavior metrics comprise: click through rate.
7. A post ranking apparatus, the apparatus comprising:
the calculation module is used for calculating the score value of each post under each detail page behavior index according to the behavior data of the user in each detail page of each post;
the first ranking module is used for calculating the ranking of each post under the detail page behavior index according to the score value of all posts under the detail page behavior index;
the determining module is used for determining the lowest ranking of each post under all the detail page behavior indexes according to the ranking of each post under each detail page behavior index;
the second sorting module is used for sorting all posts according to the determined lowest rank of each post;
the calculation module is specifically configured to count behavior data of a plurality of users in the detail page of each post in a set time period, where the behavior data of the users in the detail page of each post includes: click behavior data, browsing time data and input text data; and the number of the first and second groups,
and calculating the score value of each post under each preset detail page behavior index according to the statistical result and a preset algorithm, and normalizing the score value of each detail page behavior.
8. The post ranking apparatus of claim 7, wherein the apparatus further comprises:
the display module is used for screening out n posts according to the sorting result and a preset screening rule and displaying the n posts in a list page; wherein n is a positive integer.
9. A post ranking apparatus, the apparatus comprising: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is configured to execute a post ranking program stored in the memory to implement the steps of the post ranking method of any of claims 1 to 6.
10. A computer-readable storage medium, wherein the computer-readable storage medium stores a post ranking program;
the post ranking program, when executed by at least one processor, causes the at least one processor to perform the steps of the post ranking method of any of claims 1 to 6.
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| CN111144973B (en) * | 2019-11-29 | 2023-07-25 | 深圳市嘀哒知经科技有限责任公司 | Question ranking method and computer-readable storage medium |
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