Marketing information review method and device, electronic equipment and medium
Through a pre-trained risk assessment model, the marketing information is automatically reviewed, and the content that potentially harms consumer rights is identified and blocked, solving the problem of inefficient marketing information review and achieving efficient and accurate compliance guarantees.
Patent Information
- Application Number
- CN202510614733.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-13
- Publication Date
- 2025-08-19
AI Technical Summary
The review of marketing information in the prior art is inefficient, prone to errors, and cannot effectively protect consumer rights.
The pre-trained risk assessment model is used to automatically review marketing information, identify potential risks that harm consumer rights through deep learning algorithms and big data technology, and prevent information release when risks are detected.
It improves the efficiency and accuracy of marketing information review, reduces the risk and cost of misjudgment of manual review, and ensures information compliance and consumer rights protection.
Smart Images
Figure CN120509728A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data processing, and in particular to a method, device, electronic device, and medium for reviewing marketing information. Background Art
[0002] Currently, marketing information across all industries requires review. For example, in the financial industry, promotional copy and images for financial products require compliance review to protect consumer rights. As the volume of information increases, the workload of daily reviews increases. Current manual review processes often lead to inefficiencies. Summary of the Invention
[0003] The main purpose of the embodiments of the present application is to propose a method, device, electronic device and medium for reviewing marketing information, aiming to improve the efficiency of marketing information review.
[0004] To achieve the above objectives, a first aspect of an embodiment of the present application provides a method for reviewing marketing information, the method comprising:
[0005] Obtain marketing information for review;
[0006] inputting the marketing information into a pre-trained risk assessment model;
[0007] Obtaining risk assessment information corresponding to the marketing information output by the risk assessment model, the risk assessment information being used to indicate whether the marketing information contains information that poses a risk of damaging consumer rights;
[0008] If the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights, the marketing information is prevented from being released.
[0009] In some embodiments, obtaining risk assessment information output by the risk assessment model and corresponding to the marketing information includes:
[0010] Obtaining marketing text in the marketing information through the risk assessment model;
[0011] Extracting at least one keyword from the marketing text using the risk assessment model;
[0012] Determining a sensitive keyword among the at least one keyword using the risk assessment model;
[0013] Based on the sensitive keywords, risk assessment information corresponding to the marketing information is generated.
[0014] In some embodiments, determining a sensitive keyword in the at least one keyword using the risk assessment model includes:
[0015] Determining, by using the risk assessment model, a keyword having a target term attribute among the at least one keyword as a sensitive keyword;
[0016] The generating risk assessment information corresponding to the marketing information based on the sensitive keywords includes:
[0017] When the number of sensitive keywords determined in the at least one keyword meets a preset condition, the risk assessment information corresponding to the marketing information is determined to be the first risk assessment information, and the first risk assessment information is used to indicate that the marketing information contains information that poses a risk of damaging consumer rights.
[0018] In some embodiments, when the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights, preventing the marketing information from being published includes:
[0019] outputting a prompt message when the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights;
[0020] receiving an approval operation based on the prompt information, the approval operation being used to indicate whether to prevent the marketing information from being published;
[0021] In a case where the approval operation indicates preventing the marketing information from being released, preventing the marketing information from being released is executed.
[0022] In some embodiments, the method further comprises:
[0023] If the approval operation indicates that the marketing information is not prevented from being released, updating the risk assessment information corresponding to the marketing information to second risk assessment information, where the second risk assessment information is used to indicate that the marketing information does not contain information that poses a risk of damaging consumer rights;
[0024] constructing sample data based on the second risk assessment information and the marketing information;
[0025] The risk assessment model is trained based on the sample data.
[0026] In some embodiments, the method further comprises:
[0027] Based on the risk assessment information, modification suggestion information for information in the marketing information that has a risk of damaging consumer rights is output.
[0028] In some embodiments, inputting the marketing information into a pre-trained risk assessment model comprises:
[0029] inputting marketing information of a plurality of marketing files into the risk assessment model respectively, wherein the plurality of marketing files are associated with the same marketing task and have different file formats;
[0030] The obtaining of risk assessment information corresponding to the marketing information output by the risk assessment model includes:
[0031] Obtaining risk assessment information output by the risk assessment model for the marketing information of each marketing document, wherein the risk assessment information output by the risk assessment model for the marketing information of each marketing document includes a risk score for the marketing information of the marketing document;
[0032] The method further comprises:
[0033] multiplying the risk score of the marketing information of each marketing file by the importance weight of the corresponding file format, and adding the obtained multiple products to determine the total risk score of the marketing information included in the marketing task;
[0034] Risk assessment information corresponding to the marketing information included in the marketing task is determined according to the total risk score.
[0035] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a marketing information review device, the device comprising:
[0036] An acquisition module is used to obtain marketing information to be reviewed;
[0037] An input module, configured to input the marketing information into a pre-trained risk assessment model;
[0038] an evaluation module, configured to obtain risk assessment information corresponding to the marketing information output by the risk assessment model, wherein the risk assessment information is used to indicate whether the marketing information contains information that poses a risk of damaging consumer rights;
[0039] The blocking module is used to prevent the marketing information from being released if the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights.
[0040] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the marketing information review method described in the first aspect above.
[0041] To achieve the above-mentioned purpose, the fourth aspect of the embodiment of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the marketing information review method described in the first aspect above.
[0042] This application proposes a marketing information review method, device, electronic device, and medium. The electronic device first obtains the marketing information to be reviewed and then automatically inputs this information into a pre-trained risk assessment model, thereby enabling intelligent detection of whether the marketing information poses a risk of harming consumer rights. In actual application, the risk assessment model utilizes deep learning algorithms and big data technologies to accurately analyze the marketing information and output corresponding risk assessment information. When the risk assessment information indicates a potential risk—that is, if the marketing information contains information that poses a risk of harming consumer rights—the electronic device blocks the release of the marketing information, ensuring that non-compliant content does not enter the circulation process, thereby protecting the legitimate rights and interests of consumers. This automated review mechanism not only improves review efficiency and data processing speed, but also effectively reduces the risk of misjudgment and labor costs that may arise from manual review. In summary, by integrating risk assessment models with automated review processes, the electronic device effectively addresses the current problems of low efficiency and proneness to errors in marketing information review, effectively improving the overall level of marketing information review. BRIEF DESCRIPTION OF THE DRAWINGS
[0043] Figure 1 1 is a flowchart of a method for reviewing marketing information provided in an embodiment of the present application;
[0044] Figure 2 yes Figure 1 Flow chart of step S130;
[0045] Figure 3 yes Figure 1 Flow chart of step S140;
[0046] Figure 4 This is a flowchart of the manual approval process provided in the embodiment of the present application;
[0047] Figure 5 This is a schematic diagram of the structure of a marketing information review device provided in an embodiment of the present application;
[0048] Figure 6 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0049] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.
[0050] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.
[0051] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.
[0052] First, let’s analyze some of the terms used in this application:
[0053] Marketing information: Marketing information refers to all relevant data and content generated by a company or organization to promote its products or services, including advertisements, promotional copy, images, videos, product brochures, and various marketing materials published online. It encompasses not only traditional print and television ads but also digital marketing, such as social media posts, email outreach, and online advertising. The primary purpose of marketing information is to convey brand value, attract target customers, shape consumer perceptions of products or services, and stimulate purchase desire. In practice, marketing information must comply with relevant regulations and industry standards to ensure that the content is truthful, accurate, and not misleading, thereby protecting the legitimate rights and interests of consumers. Through effective review and management of marketing information, companies can not only improve the effectiveness of their marketing activities, but also mitigate legal risks and foster mutual trust between brands and consumers.
[0054] Artificial Intelligence Model: An AI model refers to a computational model constructed using algorithms and large amounts of data, using techniques such as machine learning and deep learning. These models can simulate human intelligent behavior and perform tasks such as pattern recognition, data analysis, decision making, and forecasting. Through data training and continuous iteration, AI models can extract useful information from massive amounts of data, identify patterns and anomalies within the data, and automatically process and judge complex problems. In fields such as marketing, finance, healthcare, and manufacturing, AI models are widely used in scenarios such as automated auditing, risk assessment, intelligent recommendations, speech recognition, and image recognition, effectively improving work efficiency and decision-making accuracy while reducing human error and operating costs. Overall, as an integral part of modern information technology, AI models provide powerful data processing and intelligent analysis capabilities for various industries, driving the optimization and innovation of business processes.
[0055] Currently, marketing information across all industries requires review. For example, in the financial industry, promotional copy and images for financial products require compliance review to protect consumer rights. As the volume of information increases, the workload of daily reviews increases. Current manual review processes often lead to inefficiencies.
[0056] Based on this, the embodiments of the present application provide a method, device, electronic device and medium for reviewing marketing information, aiming to improve the efficiency of marketing information review.
[0057] The marketing information review method, device, electronic device and medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the marketing information review method in the embodiments of the present application is described.
[0058] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.
[0059] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.
[0060] The method for reviewing marketing information provided in the embodiment of the present application relates to the field of data processing technology. The method for reviewing marketing information provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or as a server cluster or distributed system composed of multiple physical servers, or as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the method for reviewing marketing information, etc., but is not limited to the above forms.
[0061] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments in which tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media, including storage devices.
[0062] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's identity or characteristics, such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of such data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.
[0063] Figure 1 This is a flow chart of the method for reviewing marketing information provided in the embodiment of the present application. Figure 1As shown, the first aspect of the embodiment of the present application provides a method for reviewing marketing information, including steps S100 to S140.
[0064] Step S110: Acquire marketing information to be reviewed.
[0065] First, the electronic device acquires the marketing information to be reviewed. It centralizes all marketing content subject to compliance review to ensure it receives complete and authentic data. This step includes not only traditional text materials but also various media such as images and videos.
[0066] For example, when planning a credit card promotion, a bank collects all marketing information, including online ads, brochures, social media promotional copy, and related videos, for review. This centralized collection ensures that the data used in the subsequent review process is comprehensive and accurate, preventing potential risks from being missed due to missing information.
[0067] Step S120: Input the marketing information into the pre-trained risk assessment model.
[0068] The electronic device inputs the marketing information obtained above into a pre-trained risk assessment model. The pre-trained risk assessment model can be constructed based on a large amount of historical data and typical cases, and has the ability to identify the risks of damaging consumer rights and interests in marketing content.
[0069] After electronic devices input marketing information into the risk assessment model, the model can use natural language processing, image recognition and other artificial intelligence algorithms to preliminarily identify and analyze absolute terms, misleading statements or descriptions that do not comply with regulations in the content.
[0070] For example, after a bank inputs the collected credit card advertising copy into the model, the electronic device uses the model to automatically detect the vocabulary and sentence patterns in the text, and analyze whether slogans such as "lifetime no annual fee" and "zero interest rate" contain risk warnings of exaggeration or implicit conditions.
[0071] The training process for a risk assessment model begins with data collection. This requires a large amount of historical marketing information, encompassing both text and various media formats such as images and videos. The data is then preprocessed and cleaned to remove irrelevant or noisy data and standardize its format, providing a foundation for subsequent annotation. Professionals can then manually annotate each piece of marketing information to determine whether it contains risks that could harm consumer rights. This annotation process typically follows industry regulations and compliance standards, manually flagging risk factors such as exaggeration, misleading content, and absolute language. Specific risks can also be categorized into low, medium, and high risk levels, along with detailed risk descriptions and improvement recommendations. This annotated data not only covers single risk information but also provides fine-grained annotation of multiple risk points within multimedia content, such as identifying illegal symbols in images, sensitive words in text, and the compliance of spoken content in videos.
[0072] After data labeling is complete, the next stage is model training. Technicians can select appropriate machine learning or deep learning algorithms and, through supervised learning, use the labeled data as a training set, allowing the model to learn the correspondence between different risk characteristics and the labeled results. Throughout the training process, techniques such as data augmentation and sample balancing can also be introduced to compensate for insufficient data in a few high-risk samples, ensuring that the model has a strong ability to identify various risk scenarios.
[0073] Step S130: Obtain risk assessment information corresponding to the marketing information output by the risk assessment model. The risk assessment information is used to indicate whether the marketing information contains information that poses a risk of damaging consumer rights.
[0074] During this step, the electronic device obtains the risk assessment information corresponding to the marketing information output by the risk assessment model. Specifically, the electronic device provides feedback on the model analysis results in the form of a risk warning or risk score (a risk score greater than a preset threshold indicates a risk of harming consumer rights), clearly indicating whether the marketing information contains risks that may harm consumer rights and interests, and the specific location of the risk.
[0075] For example, in a bank's credit card marketing campaign, the model identified that the advertisement's use of the phrase "lifetime annual fee waiver" lacked explicit conditions and generated a risk assessment, indicating the risk of misleading consumers. This risk assessment information could include a detailed risk description, risk level, and improvement suggestions, providing a basis for further decision-making.
[0076] Step S140: If the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights, the marketing information is prevented from being released.
[0077] When risk assessment information shows that marketing information contains risks of harming consumer rights, electronic devices will prevent the marketing information from being released, ensuring that only marketing content that has undergone strict review and has controllable risks can be put into circulation, effectively reducing the risk of consumer complaints or regulatory penalties caused by non-compliance of information.
[0078] For example, if the model's risk assessment indicates a credit card advertisement contains misleading information, the electronic device will forward the information to manual review and approval, preventing the ad from being published. Only after the potential risks have been fully mitigated or manually confirmed to be risk-free will the ad be officially released, effectively protecting consumer rights and ensuring the accuracy and compliance of market information.
[0079] Through the above steps S110-S140, the electronic device first obtains the marketing information to be reviewed, and then automatically inputs this information into a pre-trained risk assessment model, thereby realizing intelligent detection of whether there is a risk of harming consumer rights in the marketing information. In actual application, the risk assessment model uses deep learning algorithms and big data technology to accurately analyze the marketing information and output corresponding risk assessment information. When the risk assessment information indicates the existence of a risk, that is, when it indicates that the marketing information contains information that poses a risk of harming consumer rights, the electronic device will block the release of the marketing information, ensuring that non-compliant content does not enter the circulation process, thereby protecting the legitimate rights and interests of consumers. Through this automated review mechanism, not only are the review efficiency and data processing speed improved, but the risk of misjudgment and labor costs that may arise from manual review are also effectively reduced. In summary, by integrating the risk assessment model and the automated review process, the electronic device effectively solves the problems of low efficiency and error-proneness in the current marketing information review, and effectively improves the overall level of marketing information review.
[0080] Figure 2 yes Figure 1 The flow chart of step S130 is as follows: Figure 2 As shown, in some embodiments, obtaining risk assessment information corresponding to marketing information output by the risk assessment model may include:
[0081] Step S210: Obtaining marketing text in the marketing information through the risk assessment model;
[0082] Step S220: extracting at least one keyword from the marketing text using the risk assessment model;
[0083] Step S230: determining a sensitive keyword among at least one keyword through a risk assessment model;
[0084] Step S240: Generate risk assessment information corresponding to the marketing information based on the sensitive keywords.
[0085] In this embodiment, the electronic device uses a risk assessment model to conduct an in-depth analysis of marketing information. It first extracts the marketing text from the marketing information. Then, based on the model's natural language processing capabilities, it automatically extracts at least one keyword from the text. It then further determines whether any of these keywords contain sensitive keywords. Ultimately, based on the identified sensitive keywords, the electronic device generates risk assessment information corresponding to the marketing information, indicating whether the marketing text contains risks that may harm consumer rights. If a certain number of sensitive keywords are present in the keywords, the electronic device may mark the risk assessment information corresponding to the marketing information as containing a certain number of sensitive keywords, i.e., as first risk assessment information indicating a risk of harming consumer rights.
[0086] In this way, electronic devices can not only automatically filter out key risk factors from marketing texts, but also generate risk warnings in a timely manner based on preset sensitive word libraries, ensuring that potential compliance risks are discovered and prevented in a timely manner before marketing information is released.
[0087] For example, when a bank launches a new credit card, its promotional copy might use the term "zero interest rate." The electronic device first extracts the complete marketing text from the ad copy, then identifies "zero interest rate" as a keyword. It further confirms that "zero interest rate" is a sensitive keyword, as the actual interest rate may be subject to additional conditions or restrictions. Based on this sensitive keyword, the risk assessment model generates corresponding risk assessment information, indicating that the credit card advertisement poses a risk of misleading consumers, requiring further review and revision of the ad content to ensure that the marketing information complies with regulatory requirements and protects consumer rights.
[0088] In some embodiments, determining a sensitive keyword in at least one keyword using a risk assessment model may include:
[0089] Using a risk assessment model, determining at least one keyword having the target term attribute as a sensitive keyword;
[0090] Generate risk assessment information corresponding to marketing information based on sensitive keywords, including:
[0091] When the number of sensitive keywords determined in at least one keyword meets a preset condition, the risk assessment information corresponding to the marketing information is determined to be the first risk assessment information, and the first risk assessment information is used to indicate that the marketing information contains information that poses a risk of damaging consumer rights.
[0092] In this embodiment, the electronic device uses a risk assessment model to conduct in-depth analysis and judgment of keywords in marketing information. During the processing, the model first identifies that there is at least one keyword with target term attributes in the marketing text, and determines the keyword as a sensitive keyword. Keywords with target term attributes include keywords that will produce multiple interpretations (i.e., there are ambiguities), keywords with overly absolute descriptions, keywords with descriptions that do not match the actual situation, and keywords with descriptions that do not comply with relevant laws and regulations.
[0093] Next, the electronic device generates risk assessment information corresponding to the marketing information based on these sensitive keywords. When the number of sensitive keywords identified in at least one keyword reaches a preset condition, the risk assessment information is determined as first risk assessment information, indicating that the marketing information contains content that poses a risk of harming consumer rights. This not only achieves precise identification of keyword attributes, but also, through the preset condition of the number of sensitive keywords, further ensures the accuracy and pertinence of the risk assessment results, and promptly alerts relevant departments to address potentially risky marketing information.
[0094] For example, a bank launches a new credit card product, and its promotional copy may include slogans such as "lifetime annual fee waiver," "zero interest rate," and "ultra-low interest rate." When processing the copy, the risk assessment model first extracts these keywords and determines whether any of them contain sensitive keywords with the attributes of the target term. For example, "zero interest rate" is identified as a sensitive keyword because it can easily mislead consumers about the preferential terms. If the number of such sensitive keywords in the copy meets the preset conditions, the electronic device generates a first risk assessment message, indicating that the credit card advertisement poses a risk of harming consumer rights and interests, and requests relevant departments to further review and revise the copy to ensure that the promotional information complies with regulatory requirements.
[0095] Figure 3 yes Figure 1 The flow chart of step S140 is as follows: Figure 3 As shown, in some embodiments, when the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights, preventing the marketing information from being released includes:
[0096] Step S310: if the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights, outputting a prompt message;
[0097] Step S320: receiving an approval operation based on the prompt information, where the approval operation is used to indicate whether to block the marketing information from being published;
[0098] Step S330: When the approval operation indicates that the marketing information is to be prevented from being released, executing the process of preventing the marketing information from being released.
[0099] Figure 4 This is a flowchart of the manual approval process provided in this application embodiment. Please refer to Figure 3-Figure 4 In this embodiment, when the risk assessment model detects that marketing information contains risks that may harm consumer rights, the electronic device automatically outputs a prompt message and, based on this, initiates the manual approval process. When the risk assessment information indicates that the marketing information is risky, the electronic device first outputs a prompt message (feeding back the risk prompt to the relevant approver and outputting the prompt message to the device terminal performing the manual approval, prompting the relevant person to perform the approval operation). Then, the electronic device receives the approval operation based on the prompt message, which indicates whether to block the release of the marketing information.
[0100] The approval operation can be carried out through a manual approval chain, which contains multiple approval nodes to ensure the accuracy and compliance of the decision. If the approval operation output by a certain approval node indicates that the marketing information is prevented from being released, the electronic device will not output a prompt message to the next approval node, directly preventing the marketing information from being released and returning the marketing information. The person who initiated the review process for the marketing information will modify the marketing information (the marketing information can start from the initiator initiating the marketing information review process and be stored in the form of a draft on the initiator's end) and resubmit it. The modified marketing information will be re-output into the risk assessment model and the entire review process will be restarted; if the approval operation output by a certain approval node indicates that the marketing information can be released, the electronic device will output a prompt message to the next approval node.
[0101] When the approval operation explicitly instructs to prevent the release of marketing information, the electronic device performs corresponding operations (such as terminating the approval process in the approval chain, or returning the marketing information to the initiator of the approval process) to prevent the marketing information from being released. Thus, under the dual protection of risk assessment and manual review, it effectively prevents potential risk information from entering the market and ensures that consumer rights are not harmed.
[0102] For example, a bank plans to publish a credit card promotion advertisement that includes slogans such as "zero interest rate" that could mislead consumers. When the risk assessment model detects this risk, the electronic device outputs a prompt message and triggers the approval process. After review by the risk management department and multiple approval nodes in the approval chain, if an approval operation at any approval node indicates that the ad is blocked, the electronic device will automatically block the ad until the content is modified and meets compliance requirements, at which point it can be resubmitted for publication, effectively protecting consumer rights.
[0103] In some embodiments, the method further comprises:
[0104] If the approval operation indicates that the marketing information is not to be prevented from being released, the risk assessment information corresponding to the marketing information is updated to second risk assessment information, where the second risk assessment information is used to indicate that the marketing information does not contain information that poses a risk of damaging consumer rights;
[0105] constructing sample data based on the second risk assessment information and the marketing information;
[0106] The risk assessment model is trained based on sample data.
[0107] In this embodiment, if the approval operation indicates that the marketing information should not be blocked, the electronic device updates the risk assessment information to the second risk assessment information to indicate that the marketing information does not contain information that poses a risk of harming consumer rights. Sample data is then constructed based on the second risk assessment information and the marketing information, and this sample data is used to train the risk assessment model. In other words, if manual approval and review determine that the marketing information does not pose a risk, the electronic device not only allows the information to be released but also feeds this result back as the second risk assessment information. This information is then combined with the marketing information to generate sample data, providing real-world examples for subsequent model training, thereby continuously optimizing the accuracy and robustness of the risk assessment model.
[0108] For example, a bank's credit card promotional advertisement, after initial testing by a risk assessment model, was manually reviewed by multiple approval nodes in the approval chain. The results determined that the ad's "ultra-low interest rate" slogan did not mislead consumers, and the approval process indicated that the ad would not be blocked. At this point, the electronic device updated the risk assessment information corresponding to the ad to a second risk assessment information, indicating that the ad did not pose a risk of harming consumer rights. Subsequently, the electronic device constructed sample data based on the ad and its updated risk assessment information, and used this data to retrain the risk assessment model, continuously improving the model's accuracy and adaptability in assessing risks in marketing information.
[0109] In some embodiments, the method further comprises:
[0110] Based on the risk assessment information, output modification suggestion information for information in marketing information that has the risk of damaging consumer rights.
[0111] In this embodiment, the electronic device uses risk assessment information to conduct an in-depth analysis of portions of marketing information that pose a risk of harming consumer rights and automatically outputs corresponding modification suggestions. Specifically, when the risk assessment model detects that marketing information poses a risk of causing consumer misunderstanding or infringing upon consumer rights, the electronic device accurately locates the risk information based on a preset sensitive vocabulary and target term attributes, and generates modification suggestions. This modification suggestion information is intended to provide marketers with specific content adjustment plans to help them improve risky descriptions, thereby eliminating or reducing potential risks and ensuring that marketing information complies with regulatory requirements and protects consumer rights before release.
[0112] For example, a bank plans to release an ad promoting a credit card that includes the term "zero interest rate." During detection, the risk assessment model identifies "zero interest rate" as a sensitive keyword and outputs risk assessment information, indicating that the term may be misleading to consumers due to the potential for additional conditions. Based on this, the electronic device automatically generates a modification suggestion, suggesting that the phrase "subject to specific conditions" be added after "zero interest rate" to clarify the actual terms of the offer. Upon receiving the modification suggestion, the bank adjusts the ad copy and resubmits it for review, ensuring that the final marketing message is both appealing to consumers and accurately reflects the product's benefits, effectively protecting consumer rights.
[0113] In some embodiments, inputting marketing information into a pre-trained risk assessment model includes:
[0114] Inputting marketing information of multiple marketing files into the risk assessment model respectively, wherein the multiple marketing files are associated with the same marketing task and the file formats of the multiple marketing files are different;
[0115] Obtain risk assessment information corresponding to marketing information output by the risk assessment model, including:
[0116] Obtain risk assessment information output by the risk assessment model for the marketing information of each marketing document, where the risk assessment information output by the risk assessment model for the marketing information of each marketing document includes a risk score for the marketing information of the marketing document;
[0117] The method also includes:
[0118] Multiply the risk score of the marketing information of each marketing file by the importance weight of the corresponding file format, and add up the multiple products obtained to determine the total risk score of the marketing information included in the marketing task;
[0119] Determine the risk assessment information corresponding to the marketing information included in the marketing task based on the total risk score.
[0120] In this embodiment, the electronic device realizes the risk judgment of the entire marketing task by inputting the marketing information of multiple marketing files into a pre-trained risk assessment model. These marketing files are all associated with the same marketing task and have different file formats (file formats may include xls, doc, jpg, jpeg, png, htm, bmp, tif, ppt, pdf, gif, mht, mpp, rtf, rar, zip, txt, log, html, docx, xlsx, pptx, etc.). The risk assessment model outputs risk assessment information for each marketing file, which includes a risk score for the marketing information of the file. Subsequently, the electronic device multiplies the risk score of each marketing file by the importance weight of the corresponding file format, and adds all the products to determine the total risk score of all marketing information included in the marketing task, and finally determines the risk assessment information corresponding to the marketing task based on the total risk score.
[0121] In this way, electronic devices can not only conduct separate risk assessments for marketing documents of different formats and contents, but also, through the introduction of file format weights, comprehensively consider the importance of various types of files in the overall marketing task, thereby more accurately reflecting the risk status of the entire marketing task.
[0122] For example, when a bank promotes a new financial product, it generates a variety of marketing files, including promotional posters (image files), advertising copy (text files), and promotional videos (video files). The electronic device inputs these three files of different formats into a pre-trained risk assessment model, and the model outputs a risk score for each file, such as a score of 0.6 for promotional posters, 0.4 for advertising copy, and 0.8 for promotional videos. Combining the importance weights of the file formats, assuming that the weights of images, text, and videos are 0.3, 0.2, and 0.5 respectively, the products of the files are 0.18, 0.08, and 0.4 respectively, and the total risk score is 0.66. Based on this total risk score, the electronic device determines the risk assessment information of the marketing task, indicating that there may be risks of harming consumer rights in the marketing information of the financial product, and thus requires further review and revision.
[0123] See also Figure 5 The present application also provides a marketing information review device that can implement the above-mentioned marketing information review method. The marketing information review device 10 includes:
[0124] An acquisition module 11 is used to acquire marketing information to be reviewed;
[0125] An input module 12, for inputting marketing information into a pre-trained risk assessment model;
[0126] An evaluation module 13 is configured to obtain risk assessment information corresponding to the marketing information output by the risk assessment model, wherein the risk assessment information is used to indicate whether the marketing information contains information that poses a risk of damaging consumer rights;
[0127] The blocking module 14 is configured to block the marketing information from being released if the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights.
[0128] The specific implementation of the marketing information review device is basically the same as the specific embodiment of the marketing information review method described above, and will not be repeated here.
[0129] The present application also provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-mentioned marketing information review method. The electronic device can be any smart terminal including a tablet computer, an in-vehicle computer, or the like.
[0130] See also Figure 6 , Figure 6 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes:
[0131] The processor 601 may be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.
[0132] The memory 602 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 602 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 602 and is called by the processor 601 to execute the marketing information review method of the embodiments of this application.
[0133] Input / output interface 603, used to implement information input and output;
[0134] Communication interface 604, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);
[0135] Bus 605 , which transmits information between various components of the device (e.g., processor 601 , memory 602 , input / output interface 603 , and communication interface 604 );
[0136] The processor 601 , the memory 602 , the input / output interface 603 and the communication interface 604 are connected to each other in communication within the device via a bus 605 .
[0137] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned marketing information review method.
[0138] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0139] The marketing information review method, device, electronic device, and medium provided in the embodiments of the present application first obtain the marketing information to be reviewed, and then automatically input this information into a pre-trained risk assessment model, thereby realizing intelligent detection of whether the marketing information poses a risk of harming consumer rights. In actual application, the risk assessment model uses deep learning algorithms and big data technology to accurately analyze marketing information and output corresponding risk assessment information. When the risk assessment information indicates the presence of a potential risk, that is, when it indicates that the marketing information contains information that poses a risk of harming consumer rights, the electronic device will block the release of the marketing information, ensuring that non-compliant content does not enter the circulation process, thereby protecting the legitimate rights and interests of consumers. Through this automated review mechanism, not only is review efficiency and data processing speed improved, but the risk of misjudgment and labor costs that may arise from manual review are effectively reduced. In summary, by integrating risk assessment models and automated review processes, the electronic device effectively solves the problems of low efficiency and proneness to errors in current marketing information review, and effectively improves the overall level of marketing information review.
[0140] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.
[0141] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.
[0142] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.
[0143] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.
[0144] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0145] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.
[0146] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.
[0147] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0148] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.
[0149] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.
[0150] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.
Claims
1. A method for reviewing marketing information, characterized in that: The method comprises: Obtain marketing information for review; inputting the marketing information into a pre-trained risk assessment model; Obtaining risk assessment information corresponding to the marketing information output by the risk assessment model, the risk assessment information being used to indicate whether the marketing information contains information that poses a risk of damaging consumer rights; If the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights, the marketing information is prevented from being released.
2. The method according to claim 1, characterized in that The obtaining of risk assessment information corresponding to the marketing information output by the risk assessment model includes: Obtaining marketing text in the marketing information through the risk assessment model; Extracting at least one keyword from the marketing text using the risk assessment model; Determining a sensitive keyword among the at least one keyword using the risk assessment model; Based on the sensitive keywords, risk assessment information corresponding to the marketing information is generated.
3. The method according to claim 2, characterized in that Determining a sensitive keyword among the at least one keyword by using the risk assessment model includes: Determining, by using the risk assessment model, a keyword having a target term attribute among the at least one keyword as a sensitive keyword; The generating risk assessment information corresponding to the marketing information based on the sensitive keywords includes: When the number of sensitive keywords determined in the at least one keyword meets a preset condition, the risk assessment information corresponding to the marketing information is determined to be the first risk assessment information, and the first risk assessment information is used to indicate that the marketing information contains information that poses a risk of damaging consumer rights.
4. The method according to claim 1, wherein When the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights, preventing the marketing information from being released includes: outputting a prompt message when the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights; receiving an approval operation based on the prompt information, the approval operation being used to indicate whether to prevent the marketing information from being published; In a case where the approval operation indicates preventing the marketing information from being released, preventing the marketing information from being released is executed.
5. The method according to claim 4, characterized in that The method further comprises: If the approval operation indicates that the marketing information is not prevented from being released, updating the risk assessment information corresponding to the marketing information to second risk assessment information, where the second risk assessment information is used to indicate that the marketing information does not contain information that poses a risk of damaging consumer rights; constructing sample data based on the second risk assessment information and the marketing information; The risk assessment model is trained based on the sample data.
6. The method according to claim 1, characterized in that The method further comprises: Based on the risk assessment information, modification suggestion information for information in the marketing information that has a risk of damaging consumer rights is output.
7. The method according to claim 1, characterized in that Inputting the marketing information into a pre-trained risk assessment model includes: inputting marketing information of a plurality of marketing files into the risk assessment model respectively, wherein the plurality of marketing files are associated with the same marketing task and have different file formats; The obtaining of risk assessment information corresponding to the marketing information output by the risk assessment model includes: Obtaining risk assessment information output by the risk assessment model for the marketing information of each marketing document, wherein the risk assessment information output by the risk assessment model for the marketing information of each marketing document includes a risk score for the marketing information of the marketing document; The method further comprises: multiplying the risk score of the marketing information of each marketing file by the importance weight of the corresponding file format, and adding the obtained multiple products to determine the total risk score of the marketing information included in the marketing task; Risk assessment information corresponding to the marketing information included in the marketing task is determined according to the total risk score.
8. A marketing information review device, characterized in that: The device comprises: An acquisition module is used to obtain marketing information to be reviewed; An input module, configured to input the marketing information into a pre-trained risk assessment model; an evaluation module, configured to obtain risk assessment information corresponding to the marketing information output by the risk assessment model, wherein the risk assessment information is used to indicate whether the marketing information contains information that poses a risk of damaging consumer rights; The blocking module is used to prevent the marketing information from being released if the risk assessment information indicates that the marketing information contains information that poses a risk of damaging consumer rights.
9. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the marketing information review method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the marketing information review method according to any one of claims 1 to 7 is implemented.