CN113836443A - Article auditing method and related equipment thereof - Google Patents
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Abstract
The embodiment of the application discloses an article auditing method, which comprises the following steps: acquiring a target article uploaded by a user and a preset label selected by the user for the target article; processing the target article by using the trained machine learning system to obtain a target label corresponding to the target article, and judging whether the target label is consistent with the preset label; and releasing the target article according to the judgment result. The embodiment of the application has the following advantages: according to the scheme, the article is processed by using the machine learning system after the label selected by the user for the target article is obtained, and the article is released based on the relation between the result obtained by processing by the machine learning system and the label pre-selected by the user, so that the release of the article is not only dependent on the preset label set by the user, and further the article classification error caused by the inaccuracy of the label selected by the user is avoided, and the reading experience of the article is improved.
Description
Technical Field
The application belongs to the technical field of computers, and particularly relates to an article auditing method and related equipment.
Background
If an article wants to be published on a network medium, the classification of the article is often required to be determined, and the article is published on a corresponding layout of the network medium based on the category information of the article, so that a user can directly obtain information required by the user through different layouts, and the information obtaining efficiency of the user is improved.
In the prior art, when a user issues an article, in order to ensure that the article passes audit in time and is acquired by other public, the user often needs to set a tag corresponding to the article, where the tag represents a category to which the article belongs, and when a network media operator receives the article, the user can directly issue the article to a corresponding layout according to the tag.
However, the label selected by the user in the article publishing mode may not be accurate enough, which easily causes the article classification error and affects the article reading experience.
Disclosure of Invention
The invention aims to provide an article auditing method, which aims to solve the problem that the existing articles are possibly classified incorrectly to influence the reading experience of the articles. A first aspect of an embodiment of the present application provides an article auditing method, including:
acquiring a target article uploaded by a user and a preset label selected by the user for the target article;
processing the target article by using a trained machine learning system to obtain a target label corresponding to the target article, wherein the trained machine learning system is obtained by training according to a plurality of historical articles and labels corresponding to the historical articles;
judging whether the target label is consistent with the preset label or not;
and releasing the target article according to the judgment result.
Based on the article auditing method provided in the first aspect of the embodiments of the present application, optionally, the issuing the target article according to the determination result includes:
if the target label is consistent with the preset label, releasing the target article according to the target label;
and if the target label is inconsistent with the preset label, converting the target article into manual review, and issuing the target article according to the review result of the manual review.
Based on the article auditing method provided in the first aspect of the embodiments of the present application, optionally, the issuing the target article according to the target tag includes:
determining the corresponding heat of the target label;
and releasing the target article according to the heat.
Based on the article auditing method provided in the first aspect of the embodiments of the present application, optionally, after the target article is published according to the determination result, the method further includes:
and adjusting the label corresponding to the target article.
Based on the article auditing method provided in the first aspect of the embodiments of the present application, optionally, the method further includes, before acquiring the target article uploaded by the user and the preset tag selected by the user for the target article:
and verifying the identity information of the user.
Based on the article auditing method provided in the first aspect of the embodiments of the present application, optionally, the preset tag includes: one or more of indoor materials, outdoor materials and household appliances.
A second aspect of the embodiments of the present application provides an article auditing apparatus, including:
the device comprises an acquisition unit, a display unit and a processing unit, wherein the acquisition unit is used for acquiring a target article uploaded by a user and a preset label selected by the user for the target article;
the processing unit is used for processing the target article by using the trained machine learning system to obtain a target label corresponding to the target article;
the judging unit is used for judging whether the target label is consistent with the preset label or not;
and the release unit is used for releasing the target article according to the judgment result.
Based on the article auditing apparatus provided in the second aspect of the embodiments of the present application, optionally, the publishing unit is specifically configured to:
if the target label is consistent with the preset label, releasing the target article according to the target label;
and if the target label is inconsistent with the preset label, converting the target article into manual review, and issuing the target article according to the review result of the manual review.
Based on the article auditing apparatus provided in the second aspect of the embodiments of the present application, optionally, the publishing unit is specifically configured to:
determining the corresponding heat of the target label;
and releasing the target article according to the heat.
Based on the article auditing apparatus provided in the second aspect of the embodiment of the present application, optionally, the publishing unit is further configured to:
and adjusting the label corresponding to the target article.
Based on the article auditing device provided in the second aspect of the embodiments of the present application, optionally, the obtaining unit is further configured to verify the identity information of the user.
Based on the article auditing device provided in the second aspect of the embodiments of the present application, optionally, the preset tag includes: one or more of indoor materials, outdoor materials and household appliances.
A third aspect of the embodiments of the present application provides an article auditing apparatus, including:
the system comprises a central processing unit, a memory, an input/output interface, a wired or wireless network interface and a power supply;
the memory is a transient memory or a persistent memory;
the central processing unit is configured to communicate with the memory, and to execute the instructions in the memory on the device to perform the method according to any one of the first aspect of the embodiments of the present application.
A fourth aspect of embodiments of the present application provides a computer-readable storage medium, including instructions, which, when executed on a computer, cause the computer to perform the method according to any one of the first aspects of embodiments of the present application.
A fifth aspect of embodiments of the present application provides a computer program product containing instructions, which when executed on a computer, cause the computer to perform the method according to any one of the first aspect of embodiments of the present application.
According to the technical scheme, the embodiment of the application has the following advantages: the scheme provides an article auditing method, which comprises the following steps: acquiring a target article uploaded by a user and a preset label selected by the user for the target article; and processing the target article by using a trained machine learning system to obtain a target label corresponding to the target article, wherein the trained machine learning system is obtained by training according to a plurality of historical articles and labels corresponding to the historical articles. Judging whether the target label is consistent with the preset label or not; and releasing the target article according to the judgment result. According to the scheme, the article is processed by using the machine learning system after the label selected by the user for the target article is obtained, and the article is released based on the relation between the result obtained by processing by the machine learning system and the label pre-selected by the user, so that the release of the article is not only dependent on the preset label set by the user, and further the article classification error caused by the inaccuracy of the label selected by the user is avoided, and the reading experience of the article is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic flow chart illustrating an embodiment of an article auditing method provided in the present application;
FIG. 2 is another schematic flow chart of an embodiment of an article auditing method provided in the present application;
FIG. 3 is a schematic structural diagram of an embodiment of an article auditing apparatus provided in the present application;
fig. 4 is another schematic structural diagram of an embodiment of an article auditing apparatus provided in the present application.
Detailed Description
In order to make the technical solutions in the embodiments of the present application better understood, the technical solutions in the embodiments of the present application are clearly and completely described below, and it is obvious that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
If an article wants to be published on a network medium, the classification of the article is often required to be determined, and the article is published on a corresponding layout of the network medium based on the category information of the article, so that a user can directly obtain information required by the user through different layouts, and the information obtaining efficiency of the user is improved. In the prior art, when a user issues an article, in order to ensure that the article passes audit in time and is acquired by other public, the user often needs to set a tag corresponding to the article, where the tag represents a category to which the article belongs, and when a network media operator receives the article, the user can directly issue the article to a corresponding layout according to the tag. However, the label selected by the user in the article publishing mode may not be accurate enough, which easily causes the article classification error and affects the article reading experience.
In order to solve the above problem, the present application provides a new article auditing method, and specifically, referring to fig. 1, an embodiment of the article auditing method provided by the present application includes: step 101-step 104.
101. The method comprises the steps of obtaining a target article uploaded by a user and a preset label selected by the user for the target article.
Specifically, the scheme can be applied to some network media or article sharing websites and the like erected on a server, such websites can be erected on a local server or a cloud server, a website system can be constructed by technologies such as java + mysql + vue and the like, and the scheme can be specifically determined according to actual conditions, and is not limited here. When the corresponding website is used, articles which a user wants to share can be uploaded through a specific interface, the articles shared by the user can be classified by a general article sharing website, so that other users can conveniently obtain contents which the user wants to browse through corresponding classification query under the article sharing website, for example, all the articles can be classified into categories such as news, novels and chats, and can be further classified into categories such as international news and foreign news under the news category, so that the user can enter the corresponding interface to browse based on the browsing requirements of the articles, the specific classification mode can be determined according to actual conditions, and the classification mode is not limited herein.
The article uploaded by the user is a target article, in order to improve the publishing efficiency of the article when the target article is uploaded, the user can select a corresponding preset label for the target article when the article is uploaded, and if the user selects to publish an article for introducing marble materials, the user can correspondingly select the preset label corresponding to the article as a 'decoration and building material' label. And after the user uploads the corresponding target article and the preset label to the website system, the next step can be executed.
102. And processing the target article by using the trained machine learning system to obtain a target label corresponding to the target article.
Specifically, the trained machine learning system is used for processing the target article to obtain a target label corresponding to the target article, and the trained machine learning system is obtained by training according to a plurality of historical articles and labels corresponding to the historical articles.
The machine learning system can be a neural network model with a fixed structure for detecting the similarity between an input decoration case and a historical decoration case, and the Neural Network (NN) is a complex network system formed by widely interconnecting a large number of simple processing units (called neurons), reflects many basic characteristics of human brain functions, and is a highly complex nonlinear dynamical learning system. Training the neural network model so that the trained neural network model can extract the labels corresponding to the target articles, specifically, the historical articles and the labels corresponding to the historical articles can be used for training so as to obtain the trained machine learning system, and the training process of the specific machine learning system can refer to the prior art, which is not repeated here specifically. And processing the target article based on the trained machine learning system, and further obtaining a target label corresponding to the article.
103. And judging whether the target label is consistent with the preset label or not.
Specifically, whether the target label is consistent with the preset label or not is judged, that is, a relationship between the target label obtained based on the processing of the machine learning system and the preset label pre-selected by the user is judged, if the target label is consistent with the preset label, the preset label selected by the user is more accurate, the preset label can be issued according to the corresponding classification set by the target label or the preset label, and if the target label is inconsistent with the preset label, a certain label of the result of the processing of the machine learning system or the preset label pre-set by the user is wrong, and further processing is required.
104. And releasing the target article according to the judgment result.
Specifically, the target article is published according to the judgment result. If the target label obtained by processing based on the machine learning system is consistent with the preset label selected by the user in advance, the target label can be published according to the corresponding classification set by the target label or the preset label, specifically, the article classification to which the target label belongs can be determined and published for the situation, and if the extracted label is 'decoration building material', the target article can be published in 'decoration column' of the article sharing website. It can be understood that, after the publishing category of the target article is determined, the rank of the target article in the category can be determined based on the tag corresponding to the target article, if a certain tag of the target article is a hotspot tag, it is determined that the rank of the target article in the category is higher, and a specific publishing manner may be determined according to an actual situation, which is not limited herein.
If the target label obtained by the machine learning system processing is inconsistent with the preset label pre-selected by the user, it indicates that an error exists in one of the target label and the preset label pre-set by the user, and further processing is required. Specifically, the further processing mode may be to adopt a manual review mode to review the target article, or may be to release the target article based on a result processed by the machine learning system, and the specific further processing mode may be determined according to an actual situation, which is not limited herein.
According to the technical scheme, the embodiment of the application has the following advantages: the scheme provides an article auditing method, which comprises the following steps: acquiring a target article uploaded by a user and a preset label selected by the user for the target article; and processing the target article by using a trained machine learning system to obtain a target label corresponding to the target article, wherein the trained machine learning system is obtained by training according to a plurality of historical articles and labels corresponding to the historical articles. Judging whether the target label is consistent with the preset label or not; and releasing the target article according to the judgment result. According to the scheme, the article is processed by using the machine learning system after the label selected by the user for the target article is obtained, and the article is released based on the relation between the result obtained by processing by the machine learning system and the label pre-selected by the user, so that the release of the article is not only dependent on the preset label set by the user, and further the article classification error caused by the inaccuracy of the label selected by the user is avoided, and the reading experience of the article is improved.
Based on the embodiment corresponding to fig. 1, optionally, the present application further provides a more detailed embodiment that can be implemented selectively, please refer to fig. 2, where an embodiment of an auditing method of an article of the present application includes: step 201-step 210.
201. And verifying the identity information of the user.
Specifically, before the article is published, the identity information of the user can be verified, and whether the user has the right to publish the article is verified, for example, the user with a specific identity can be set to have the right to publish the article, and before the user publishes the article, the identity information of the user needs to be verified, and whether the user meets the requirement of the specific identity is verified. Specifically, the verification method may be determined according to actual situations, and is not limited herein.
202. The method comprises the steps of obtaining a target article uploaded by a user and a preset label selected by the user for the target article.
203. And processing the target article by using the trained machine learning system to obtain a target label corresponding to the target article.
204. And judging whether the target label is consistent with the preset label or not.
Specifically, the steps 202 to 204 are similar to the steps 101 to 103 in the embodiment of fig. 1, and are not repeated herein. If the target label is consistent with the preset label, executing step 205, determining the corresponding heat of the target label, if the target label is inconsistent with the preset label, executing step 207, converting the target article into manual review, and issuing the target article according to the review result of the manual review.
205. And determining the corresponding heat of the target label.
Specifically, under the condition that the target label is consistent with the preset label, the heat of the target label corresponding to the target article is determined, different heat information can be preset for different labels, the heat is determined according to user activity data of a website system in a previous period of time, specifically, the click rate of an article category with a certain label is higher, the label can be correspondingly set to have higher heat, the heat corresponding to the article with lower click rate is set to be lower, and the specific heat setting mode can be set to be not limited according to the actual situation.
206. And releasing the target article according to the heat.
Specifically, the target article is released according to the popularity. If the extracted label is 'decoration building material', the target article can be released in a 'decoration column' under the article sharing website. Under the classification, if the popularity of the target label corresponding to the target article search is high, the article is set to be high in the sequence under the decoration column, so that other users can obtain hot content in time, and user experience is improved.
207. And converting the target article into manual review, and issuing the target article according to the review result of the manual review.
Specifically, if the target label is inconsistent with the preset label, the target article is converted into manual review, and the target article is issued according to the review result of the manual review. The manual review has higher accuracy, the manually determined label corresponding to the target article can be obtained after the manual review process is completed, and the manually determined label may be consistent with any one of the target label or the preset label or inconsistent with both of the target label and the preset label, which is determined according to the actual situation. After the tag corresponding to the target article is manually determined, the target article can be published according to the determined tag, and the specific article publishing process can be similar to that in steps 205 to 206, which is not described herein in detail.
208. And adjusting the label corresponding to the target article.
Specifically, this step is executed after the target article is published, and after the target article is published, there may be a case where the preset tag selected by the user and the target tag obtained based on the machine learning system are both wrong, and at this time, the article is published, so that the tag corresponding to the target article can be manually adjusted, and the article publishing policy can be correspondingly adjusted, that is, the classification to which the article belongs can be correspondingly adjusted, which is specifically determined according to the actual situation, and is not limited here.
According to the technical scheme, the embodiment of the application has the following advantages: the scheme provides an article auditing method, which comprises the following steps: acquiring a target article uploaded by a user and a preset label selected by the user for the target article; and processing the target article by using a trained machine learning system to obtain a target label corresponding to the target article, wherein the trained machine learning system is obtained by training according to a plurality of historical articles and labels corresponding to the historical articles. Judging whether the target label is consistent with the preset label or not; and releasing the target article according to the judgment result. According to the scheme, the article is processed by using the machine learning system after the label selected by the user for the target article is obtained, and the article is released based on the relation between the result obtained by processing by the machine learning system and the label pre-selected by the user, so that the release of the article is not only dependent on the preset label set by the user, and further the article classification error caused by the inaccuracy of the label selected by the user is avoided, and the reading experience of the article is improved.
The above description describes an article auditing method provided by the present application, and referring to fig. 3, an embodiment of the article auditing apparatus provided by the present application includes:
an obtaining unit 301, configured to obtain a target article uploaded by a user and a preset tag selected by the user for the target article;
a processing unit 302, configured to process the target article using a trained machine learning system, to obtain a target tag corresponding to the target article;
a judging unit 303, configured to judge whether the target tag is consistent with the preset tag;
and the issuing unit 304 is used for issuing the target article according to the judgment result.
Optionally, the publishing unit 304 is specifically configured to:
if the target label is consistent with the preset label, releasing the target article according to the target label;
and if the target label is inconsistent with the preset label, converting the target article into manual review, and issuing the target article according to the review result of the manual review.
Optionally, the publishing unit 304 is specifically configured to:
determining the corresponding heat of the target label;
and releasing the target article according to the heat.
Optionally, the issuing unit 304 is further configured to:
and adjusting the label corresponding to the target article.
Optionally, the obtaining unit 301 is further configured to verify identity information of the user.
Optionally, the preset tag includes: one or more of indoor materials, outdoor materials and household appliances.
In this embodiment, the flow executed by each unit in the article auditing apparatus is similar to the method flow described in the embodiment corresponding to fig. 1 or fig. 2, and is not described again here.
According to the technical scheme, the embodiment of the application has the following advantages: this scheme provides an article audit equipment, includes: an obtaining unit 301, configured to obtain a target article uploaded by a user and a preset tag selected by the user for the target article; a processing unit 302, configured to process the target article using a trained machine learning system, to obtain a target tag corresponding to the target article; a judging unit 303, configured to judge whether the target tag is consistent with the preset tag; and the issuing unit 304 is used for issuing the target article according to the judgment result. According to the scheme, the article is processed by using the machine learning system after the label selected by the user for the target article is obtained, and the article is released based on the relation between the result obtained by processing by the machine learning system and the label pre-selected by the user, so that the release of the article is not only dependent on the preset label set by the user, and further the article classification error caused by the inaccuracy of the label selected by the user is avoided, and the reading experience of the article is improved.
Fig. 4 is a schematic structural diagram of an article auditing apparatus according to an embodiment of the present application, where the article auditing apparatus 400 may include one or more Central Processing Units (CPUs) 401 and a memory 405, where the memory 405 stores one or more application programs or data.
In this embodiment, the specific functional module division in the central processing unit 401 may be similar to the functional module division manner of each unit described in the foregoing fig. 4, and is not described here again.
The article review apparatus 400 may also include one or more power supplies 402, one or more wired or wireless network interfaces 403, one or more input-output interfaces 404, and/or one or more operating systems, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.
The central processing unit 401 may perform the operations performed by the article auditing method in the embodiment shown in fig. 1, which are not described herein again.
Embodiments of the present application further provide a computer storage medium for storing computer software instructions for the article auditing method, where the computer storage medium includes a program designed for executing the article auditing method.
The article auditing method may be as described in the article auditing method described in fig. 1 or fig. 2 above.
An embodiment of the present application further provides a computer program product, where the computer program product includes computer software instructions, and the computer software instructions may be loaded by a processor to implement the flow of the article auditing method in any one of fig. 1 and fig. 2.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, equivalent circuit transformations, partitions of units, and logic functions may be merely one type of partitioning, and in actual implementation, there may be other partitioning manners, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents or improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An article auditing method, comprising:
acquiring a target article uploaded by a user and a preset label selected by the user for the target article;
processing the target article by using a trained machine learning system to obtain a target label corresponding to the target article, wherein the trained machine learning system is obtained by training according to a plurality of historical articles and labels corresponding to the historical articles;
judging whether the target label is consistent with the preset label or not;
and releasing the target article according to the judgment result.
2. The article auditing method of claim 1, wherein said publishing the target article according to the determination comprises:
if the target label is consistent with the preset label, releasing the target article according to the target label;
and if the target label is inconsistent with the preset label, converting the target article into manual review, and issuing the target article according to the review result of the manual review.
3. The article auditing method of claim 2, wherein said publishing the target article according to the target tag comprises:
determining the corresponding heat of the target label;
and releasing the target article according to the heat.
4. The article auditing method according to claim 1, wherein after the target article is published according to the determination result, the method further comprises:
and adjusting the label corresponding to the target article.
5. The article auditing method according to claim 1, wherein the method further comprises, before obtaining a target article uploaded by a user and a preset tag selected by the user for the target article:
and verifying the identity information of the user.
6. An article auditing method according to claim 1, wherein the preset tag includes: one or more of indoor materials, outdoor materials and household appliances.
7. An article auditing apparatus, comprising:
the device comprises an acquisition unit, a display unit and a processing unit, wherein the acquisition unit is used for acquiring a target article uploaded by a user and a preset label selected by the user for the target article;
the processing unit is used for processing the target article by using the trained machine learning system to obtain a target label corresponding to the target article;
the judging unit is used for judging whether the target label is consistent with the preset label or not;
and the release unit is used for releasing the target article according to the judgment result.
8. An article auditing apparatus, comprising:
the system comprises a central processing unit, a memory, an input/output interface, a wired or wireless network interface and a power supply;
the memory is a transient memory or a persistent memory;
the central processor is configured to communicate with the memory, the instructions in the memory being executable on the central processor to perform the method of any of claims 1 to 6.
9. A computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the method of any one of claims 1 to 6.
10. A computer program product comprising instructions which, when run on a computer, cause the computer to perform the method of any one of claims 1 to 6.
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