Abnormal copywriting rewriting method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides an abnormal document rewriting method and device, electronic equipment and a storage medium, belongs to the technical field of text processing, and is suitable for the field of financial science and technology. The method comprises the following steps: acquiring copywriting evaluation guide data; performing feature extraction on preset target copywriting data to obtain copywriting features; performing copywriting classification on the target copywriting data based on the copywriting features to obtain copywriting categories; based on the copywriting category and the copywriting feature, screening a preset review indication template library to obtain a copywriting review indication text; based on the copywriting review indication text, performing information extraction on the copywriting evaluation guide data to obtain a copywriting evaluation index; based on the copywriting evaluation index, performing copywriting content anomaly detection on the target copywriting data to obtain copywriting content anomaly information; and rewriting the target copywriting data based on the copywriting content exception information. According to the embodiment of the invention, the accuracy of rewriting the abnormal copywriting can be improved.

Description

Technical Field

[0001] The present application relates to the field of text processing technology, is applicable to the field of financial technology, and in particular to a method and device for rewriting abnormal text, an electronic device, and a storage medium. Background Art

[0002] Copy review is the inspection and evaluation of copy content to ensure its accuracy, compliance, clarity and appropriateness. For example, in the financial sector, by reviewing financial product promotional copy, anomalies in the copy can be discovered, making it easier for financial industry staff to rewrite the copy to improve its accuracy, compliance, clarity and appropriateness.

[0003] At present, the common method of rewriting abnormal texts is to modify the abnormal texts found by manual review. This method is easily affected by subjective factors and it is difficult to ensure the accuracy of the text rewriting, which may lead to errors in the rewritten texts. Therefore, how to improve the accuracy of abnormal text rewriting has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to provide a method and device for rewriting abnormal text, an electronic device and a storage medium, aiming to improve the accuracy of rewriting abnormal text.

[0005] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes a method for rewriting abnormal text, the method comprising:

[0006] Get copywriting assessment guide data;

[0007] Extract features from preset target copywriting data to obtain copywriting features;

[0008] Classifying the target copy data based on the copy features to obtain a copy category;

[0009] Performing a copy analysis on the copy features to obtain basic copy information, and screening a preset review instruction template library based on the copy category and the basic copy information to obtain a copy review instruction text;

[0010] Based on the copy review instruction text, extract information from the copy evaluation guide data to obtain a copy evaluation index;

[0011] Based on the copy evaluation index, the target copy data is subjected to copy content anomaly detection to obtain copy content anomaly information;

[0012] Based on the abnormal content information of the copy, the target copy data is rewritten.

[0013] In some embodiments, the process of performing text content anomaly detection on the target text data based on the text evaluation index to obtain text content anomaly information includes:

[0014] Performing sentiment analysis on the target copywriting data to obtain the copywriting sentiment;

[0015] Based on the copy evaluation index, the copy emotion is evaluated to obtain abnormal copy emotion information;

[0016] Performing word segmentation processing on the target copywriting data to obtain copywriting phrases;

[0017] Based on the copy evaluation index, performing phrase anomaly detection on the copy phrase to obtain copy abnormal phrase information;

[0018] Based on the copywriting phrases and the copywriting evaluation index, grammatical anomaly detection is performed on the target copywriting data to obtain copywriting abnormal grammatical information;

[0019] The abnormal sentiment information of the copy, the abnormal phrase information of the copy and the abnormal grammatical information of the copy are merged to obtain the abnormal content information of the copy.

[0020] In some embodiments, performing phrase anomaly detection on the copy phrase based on the copy evaluation index to obtain copy abnormal phrase information includes:

[0021] Performing phrase interpretation on the copywriting phrases to obtain the phrase meanings;

[0022] Based on the meaning of the phrase, the copywriting phrase is screened to obtain a target phrase;

[0023] Based on the text evaluation index, the target phrase is tested for phrase standardization to obtain the abnormal phrase information of the text.

[0024] In some embodiments, the performing grammatical anomaly detection on the target copy data based on the copy phrase and the copy evaluation index to obtain copy abnormal grammatical information includes:

[0025] Performing phrase analysis on the copywriting phrase to obtain the phrase part of speech;

[0026] Based on the word group part of speech, the target copywriting data is parsed to obtain the copywriting grammar;

[0027] Based on the text evaluation index, the text grammar is checked for grammatical standardization to obtain abnormal grammatical information of the text.

[0028] In some embodiments, the classifying the target copy data based on the copy features to obtain the copy category includes:

[0029] Performing feature mapping on the copy feature to obtain a feature category and a category confidence, wherein the category confidence is used to indicate the degree of credibility of the copy feature being the feature category;

[0030] Based on the category confidence text feature, the feature category is selected to obtain the text category.

[0031] In some embodiments, extracting information from the copywriting evaluation guide data based on the copywriting review instruction text to obtain the copywriting evaluation index includes:

[0032] Extracting audit information from the copy review instruction text to obtain key points for rewriting abnormal copy;

[0033] Based on the abnormal copy rewriting key points, the copy evaluation guide data is screened to obtain the copy evaluation index.

[0034] In some embodiments, rewriting the target copy data based on the copy content abnormality information includes:

[0035] Performing natural language processing on the target copywriting data to obtain copywriting context information;

[0036] Based on the abnormal information of the copy content, abnormal location is performed on the target copy data to obtain the abnormal information location;

[0037] Based on the text context information, the text at the abnormal information location is modified to obtain a standard text.

[0038] To achieve the above-mentioned purpose, a second aspect of the embodiments of the present application provides an abnormal text rewriting device, the device comprising:

[0039] Evaluation guide acquisition module, used to obtain copywriting evaluation guide data;

[0040] The copy category prediction module is used to classify the preset target copy data to obtain the copy category;

[0041] An instruction text generation module, used to generate a copy review instruction text based on the copy category;

[0042] An evaluation index extraction module, used to extract information from the copywriting evaluation guide data based on the copywriting review instruction text to obtain a copywriting evaluation index;

[0043] A copy anomaly detection module, used to perform copy content anomaly detection on the target copy data based on the copy evaluation index to obtain copy content anomaly information;

[0044] The abnormal text rewriting module is used to rewrite the target text data based on the abnormal information of the text content.

[0045] To achieve the above objectives, a 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, the method described in the first aspect is implemented.

[0046] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0047] The abnormal copywriting rewriting method and device, electronic device and storage medium proposed in the present application establish the review standard of the copy by acquiring the copy evaluation guide data, then extracting the features of the preset target copy data to obtain the copy features, and classifying the target copy data according to the copy features to identify the field to which the target copy data belongs, then parsing the copy features to obtain the basic copy information, and based on the copy category and the basic copy information, screening the preset review instruction template library to obtain the copy review instruction text, and providing targeted instructions for the copy review system, then extracting the key copy evaluation indicators from the copy evaluation guide data, using the copy evaluation indicators to perform anomaly detection on the target copy data, and identifying non-compliant or inaccurate content, and finally, performing necessary rewriting on the copy according to the detection results to ensure its accuracy, compliance, clarity and appropriateness, thereby reducing the subjectivity of manual review and improving the accuracy of abnormal copy rewriting. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of an abnormal text rewriting method provided in an embodiment of the present application;

[0049] Figure 2 yes Figure 1 Flow chart of step S102 in FIG.

[0050] Figure 3 yes Figure 1 Flow chart of step S105 in FIG.

[0051] Figure 4 yes Figure 1 Flow chart of step S106 in FIG.

[0052] Figure 5 yes Figure 4 Flow chart of step S404 in FIG.

[0053] Figure 6 yes Figure 4 Flow chart of step S405 in FIG.

[0054] Figure 7 yes Figure 1 Flow chart of step S107 in FIG.

[0055] Figure 8 It is a structural schematic diagram of an abnormal text rewriting device provided in an embodiment of the present application;

[0056] Fig. 9 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0058] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0060] First, some nouns involved in this application are analyzed:

[0061] Copy Review System: The copy review system is an advanced natural language processing technology designed specifically for the financial sector to automate and accurately check the compliance of copywriting. The system first obtains and analyzes the copy evaluation guide data of the financial industry, and then intelligently classifies the target copy data to determine its category, such as investment products or insurance services. Based on the copy category, the system generates customized copy review instruction texts, which guide the system to extract key copy evaluation indicators from the evaluation guide. Then, the system uses these indicators to conduct in-depth anomaly detection on the copy, including sentiment analysis, word segmentation, phrase anomaly detection, and grammatical anomaly detection to identify and locate potential problems in the copy. Once anomalies are found, such as overly optimistic emotional expressions or non-compliant phrases, the system will automatically or suggest copy rewriting to ensure that the copy meets industry requirements in terms of emotional expression, word accuracy, and grammatical standardization. Through this process, the copy review system not only improves the compliance and professionalism of the copy, but also improves the efficiency and consistency of the review by reducing the subjectivity of manual review, providing a strong guarantee for the quality of financial copywriting and consumer rights.

[0062] Natural language processing technology: Natural language processing technology is an important branch of artificial intelligence, which focuses on enabling computers to understand, interpret, generate and respond to human language, including text and voice. This technology involves a variety of algorithms and models, and is able to perform tasks such as text analysis, sentiment analysis, machine translation, speech recognition and generation. The core challenge of natural language processing technology lies in the complexity of language, including grammar, semantics, context and cultural differences. Through deep learning, machine learning and other advanced computing methods, natural language processing systems are able to learn language patterns from large amounts of data and continuously optimize their performance to achieve more natural and accurate language interactions. In many fields such as finance, healthcare, customer service, etc., natural language processing technology is widely used to improve efficiency, enhance user experience and promote automated decision-making processes.

[0063] Copy review is the inspection and evaluation of copy content to ensure its accuracy, compliance, clarity and appropriateness. For example, in the financial sector, by reviewing financial product promotional copy, anomalies in the copy can be discovered, making it easier for financial industry staff to rewrite the copy to improve its accuracy, compliance, clarity and appropriateness.

[0064] At present, the common method of rewriting abnormal texts is to modify the abnormal texts found by manual review. This method is easily affected by subjective factors and it is difficult to ensure the accuracy of the text rewriting, which may lead to errors in the rewritten texts. Therefore, how to improve the accuracy of abnormal text rewriting has become a technical problem that needs to be solved urgently.

[0065] Based on this, the embodiments of the present application provide a method and device for rewriting abnormal text, an electronic device and a storage medium, aiming to improve the accuracy of rewriting abnormal text.

[0066] The abnormal text rewriting method and device, electronic device and storage medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the abnormal text rewriting method in the embodiments of the present application is described.

[0067] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, 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 obtain the best results.

[0068] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0069] The abnormal text rewriting method provided in the embodiment of the present application relates to the field of text processing technology and is applicable to the field of financial technology. The abnormal text rewriting method provided in the embodiment of the present application can be applied to the terminal, can also be applied to the server side, and can also be software running in the terminal or the 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 it can be configured as a server cluster or a distributed system composed of multiple physical servers, and can also be configured 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 abnormal text rewriting method, etc., but is not limited to the above forms.

[0070] 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, etc. 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, etc. 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 through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0071] Figure 1 This is an optional flow chart of the abnormal copywriting method provided in the embodiment of the present application, which is applied to the copy review system. Figure 1 The method may include but is not limited to steps S101 to S107.

[0072] Step S101, obtaining copywriting evaluation guide data;

[0073] Step S102, extracting features from preset target copy data to obtain copy features;

[0074] Step S103, classifying the target copy data based on the copy features to obtain a copy category;

[0075] Step S104, parsing the copy features to obtain basic copy information, and screening a preset review instruction template library based on the copy category and the basic copy information to obtain a copy review instruction text;

[0076] Step S105, based on the copy review instruction text, extract information from the copy evaluation guide data to obtain the copy evaluation index;

[0077] Step S106, based on the copy evaluation index, the target copy data is subjected to copy content anomaly detection to obtain copy content anomaly information;

[0078] Step S107: rewrite the target copy data based on the copy content abnormality information.

[0079] In steps S101 to S107 shown in the embodiment of the present application, the copy review system obtains copy evaluation guide data, performs feature extraction on preset target copy data to obtain copy features, and classifies the target copy data according to the copy features to obtain copy categories. Furthermore, the copy features are analyzed to obtain basic copy information, and based on the copy categories and basic copy information, a preset review instruction template library is screened to obtain a copy review instruction text. Secondly, based on the copy review instruction text, information is extracted from the copy evaluation guide data to obtain copy evaluation indicators. Based on the copy evaluation indicators, the target copy data is detected for copy content anomalies to obtain copy content anomaly information. Finally, based on the copy content anomaly information, the target copy data is rewritten. Therefore, the present application establishes the review standards for the copy by acquiring the copy evaluation guide data, then performs feature extraction on the preset target copy data to obtain the copy features, and classifies the target copy data according to the copy features to identify the field to which the target copy data belongs, then performs copy analysis on the copy features to obtain the basic copy information, and based on the copy category and the basic copy information, screens the preset review instruction template library to obtain the copy review instruction text, and provides targeted instructions for the copy review system, and then extracts key copy evaluation indicators from the copy evaluation guide data, and uses the copy evaluation indicators to perform anomaly detection on the target copy data to identify non-compliant or inaccurate content, and finally, performs necessary rewriting of the copy based on the detection results to ensure its accuracy, compliance, clarity and appropriateness, thereby reducing the subjectivity of manual review and improving the accuracy of abnormal copy rewriting.

[0080] In step S101 of some embodiments, the copy evaluation guide data refers to the rules and standards used to guide the copy review process. For example, in a financial copy scenario, the copy evaluation guide data may be insurance industry regulatory rules, advertising laws, company legal compliance requirements, etc.

[0081] This application can crawl the laws and regulations of the terminology evaluation documents on the Internet through a pre-set web crawler script to obtain the document evaluation information, and then use the document review system to organize the document evaluation information to obtain the document evaluation guide data.

[0082] In step S102 of some embodiments, the target copy data refers to a newly written copy to be reviewed, for example, in an insurance promotion scenario, a health insurance promotion copy just written by an insurance salesperson. The copy category can be determined based on the copy content of the target copy data. For example, when the copy content of the target copy data mainly introduces the advantages of health insurance, the copy category of the target copy data can be a health insurance promotion copy.

[0083] In an embodiment of the present application, the copy review system can use natural language processing technology to perform content analysis on the target copy data, thereby extracting the copy features of the target copy data, wherein the natural language processing technology includes text segmentation, named entity recognition, grammatical parsing, semantic parsing and other processes. For a target copy data about "high-yield investment plan", feature extraction may identify keywords such as "high yield", "investment plan", "return rate", and named entities such as "financial products" and "market trends".

[0084] It should be noted that the copy features extracted by the above-mentioned natural language processing technology can be keywords, phrases, named entities, semantic roles, etc. in the target copy data, as well as the distribution and frequency of occurrence of keywords, phrases, named entities, semantic roles, etc. in the target copy data.

[0085] In step S103 of some embodiments, a category confidence can be assigned to each copy feature through a deep learning model. This confidence reflects the degree of credibility that the copy feature belongs to a certain feature category. Subsequently, the copy review system screens the copy features according to these category confidences, selects feature categories with higher confidence, and finally determines the copy category of the target copy data.

[0086] For details, see Figure 2 In some embodiments, step S103 may include but is not limited to steps S201 to S202:

[0087] Step S201, feature mapping is performed on the copy feature to obtain a feature category and a category confidence, wherein the category confidence is used to indicate the degree of credibility of the copy feature as a feature category;

[0088] Step S202: Based on the category confidence text feature, a feature category is selected to obtain a text category.

[0089] In step S201 and step S202 of some embodiments, after obtaining the copy features in the target copy data, the copy review system can predict the category of the target copy data through a machine learning model or a deep learning model. In detail, the machine learning model or the deep learning model can parse the copy features and then combine the text information of the target copy data to predict the probability that the target copy data is a certain feature category, that is, the category confidence, and then use the feature category with the highest category confidence as the copy category of the target copy data. For example, in the financial field, a trained deep learning model may classify the above-mentioned "high-yield investment plan" target copy data into the "investment product promotion" category.

[0090] In steps S201 to S202 shown in the present embodiment, feature mapping is performed on the copy features to obtain feature categories and category confidences, wherein the category confidence is used to indicate the degree of credibility of the copy features as feature categories. Furthermore, based on the category confidence copy features, feature categories are selected to obtain copy categories, thereby reducing errors and subjective biases in manual copy classification, and by ensuring the objectivity and consistency of copy classification, a solid foundation is provided for generating customized copy review instruction texts. In addition, the automated copy classification of the copy review system improves the accuracy of copy content anomaly detection, thereby facilitating timely discovery and correction of non-compliant content in the copy, and ensuring that the copy complies with industry standards and regulatory requirements before publication.

[0091] In step S104 of some embodiments, the review instruction template library is a pre-built database for storing review instruction templates, and the review instruction template library contains review instruction templates for different document categories, wherein the review instruction template is used to guide the document review system to perform document review to ensure the content compliance and accuracy of the target document.

[0092] This application can use natural language processing technology to deeply analyze the target copy and extract key basic copy information, such as core keywords, phrases and named entities. Then, based on the above copy category, the copy review system can filter out the review instruction text template that is most relevant to the copy category from the pre-built review instruction template library, where the review instruction text template contains the review points and standards for the copy category. Then, combined with the basic copy information of the target copy, the screened review instruction template is customized to generate the final copy review instruction text. The copy review instruction text will guide the review procedure in the copy review system to conduct a detailed review of the target copy to ensure the content compliance, accuracy and appropriateness of the target copy.

[0093] In step S105 of some embodiments, the subsequent program body in the copy review system can obtain the key points of abnormal copy rewriting by extracting the key information in the copy review instruction text, and then filter the copy evaluation information in the above copy evaluation guide data according to the key points of abnormal copy rewriting, so as to obtain the copy evaluation index.

[0094] For details, see Figure 3 In some embodiments, step S105 may include but is not limited to steps S301 to S302:

[0095] Step S301, extracting audit information from the copy review instruction text to obtain key points for abnormal copy rewriting;

[0096] Step S302, based on the abnormal copy rewriting key points, the copy evaluation guide data is screened to obtain the copy evaluation index.

[0097] In step S301 of some embodiments, by performing text parsing and context understanding on the copy review instruction text, potential problems of the target copy data described in the copy review instruction text can be identified. Furthermore, the potential problems of the target copy data are sorted out to obtain key points for rewriting abnormal copy.

[0098] It is important to know that abnormal key points in copywriting can be non-compliant statements, misleading information, or content that requires further clarification in the target copywriting data. For example, when the copywriting review instruction text points out that attention should be paid to the statement of "return on investment", then the "guaranteed high returns" in the target copywriting data may be considered as abnormal copywriting rewriting key points that mislead investors into believing that there is no risk in investment.

[0099] In step S302 of some embodiments, after extracting the abnormal copy rewriting key points in the copy review instruction text, the copy review system can filter out the copy evaluation information related to the abnormal copy rewriting key points from the copy evaluation guide data, thereby obtaining the copy evaluation indicators. For example, for the above-mentioned abnormal copy rewriting key point "guarantee high returns", the copy evaluation guide data may provide an indicator of "avoiding the use of absolute or misleading expressions". At this time, the copy evaluation indicators may include "ensuring that all investment-related expressions comply with the principle of authenticity and do not use words such as "guarantee" and "absolute".

[0100] In steps S301 to S302 shown in the present embodiment, by extracting audit information from the copy review instruction text, key points for rewriting abnormal copy are obtained. Furthermore, based on the key points for rewriting abnormal copy, information on the copy evaluation guide data is screened to obtain copy evaluation indicators, which greatly improves the pertinence and efficiency of copy review, reduces subjective judgment errors in the manual review process, and enhances the compliance and transparency of the copy.

[0101] In step S106 of some embodiments, by performing natural language processing on the target copy data, copy information such as copy sentiment, copy phrases and copy grammar of the target copy data can be obtained, and then according to the copy evaluation indicators, the copy anomaly evaluation is performed on the above copy information such as copy sentiment, copy phrases and copy grammar to determine whether the target copy data has copy sentiment anomalies, copy phrase anomalies, copy grammar anomalies, etc. Furthermore, the copy review system summarizes the above judgment results to obtain copy content abnormality information.

[0102] For details, see Figure 4In some embodiments, step S106 may include but is not limited to steps S401 to S406:

[0103] Step S401, performing sentiment analysis on the target copy data to obtain the copy sentiment;

[0104] Step S402, based on the copy evaluation index, evaluate the copy emotion to obtain abnormal copy emotion information;

[0105] Step S403, performing word segmentation processing on the target copywriting data to obtain copywriting phrases;

[0106] Step S404, based on the copy evaluation index, perform phrase anomaly detection on the copy phrases to obtain copy abnormal phrase information;

[0107] Step S405, based on the copy phrases and copy evaluation indicators, perform grammatical anomaly detection on the target copy data to obtain copy abnormal grammatical information;

[0108] Step S406, merging the abnormal sentiment information of the copy, the abnormal phrase information of the copy and the abnormal grammatical information of the copy to obtain the abnormal content information of the copy.

[0109] In step S401 of some embodiments, sentiment analysis is to identify and extract sentiment tendencies in the text through natural language processing technology.

[0110] The present application can utilize sentiment recognition tools or algorithms to perform phrase analysis on words or phrases in the target copy data, thereby determining the sentiment tendency of the target copy data, i.e., the copy sentiment, wherein the sentiment tendency includes positive, negative, or neutral. For example, for the sentence "Invest in our fund and enjoy unprecedented growth" in the target copy data of financial product promotion, the sentiment recognition tool may identify "enjoy" and "growth" as positive sentiment words.

[0111] In step S402 of some embodiments, text sentiment evaluation refers to further determining whether the sentiment expression of the target text data is appropriate and whether it meets the compliance requirements of the text evaluation indicators based on the result of sentiment analysis.

[0112] This application can determine the compliant copywriting sentiment tendency based on the copywriting evaluation indicators, and then compare the above copywriting sentiment with the compliant copywriting sentiment tendency, so as to determine whether the copywriting sentiment is abnormal, and generate copywriting abnormal sentiment information when the copywriting sentiment is abnormal. For example, according to the copywriting evaluation indicators of the financial industry, the target copywriting data must not be overly optimistic or pessimistic. If words or phrases such as "enjoy" and "unprecedented growth" that indicate overly optimistic emotions appear in the target copywriting data, it can be determined that the copywriting sentiment of the target copywriting data is abnormal, thereby generating copywriting abnormal sentiment information.

[0113] It is important to know that the abnormal sentiment information of the copy includes the words or phrases in which the sentiment of the copy is incorrect, and the reasons for the error are marked.

[0114] In step S403 of some embodiments, word segmentation processing is to decompose the target text data into separate words or phrases so as to perform a more detailed analysis of the target text data.

[0115] The present application can utilize a word segmentation algorithm to decompose the target copy data, thereby obtaining separate words or phrases, namely, copy phrases. For example, by performing word segmentation processing on the target copy data "our investment services provide personalized consulting", the target copy data can be decomposed into copy phrases such as "our", "investment services", "provide", and "personalized consulting".

[0116] In step S404 of some embodiments, phrase anomaly detection is to identify whether a text phrase in the target text data meets the text evaluation index.

[0117] The present application can determine the meaning of the copywriting phrases by interpreting the copywriting phrases in detail, and then screen out the target phrases related to the copywriting evaluation indicators according to the phrase meanings. Finally, the target phrases are subjected to normative detection to identify abnormal phrases that do not meet the copywriting evaluation indicators, and the copywriting abnormal phrase information is generated according to the abnormal phrases.

[0118] For details, see Figure 5 In some embodiments, step S404 may include but is not limited to steps S501 to S503:

[0119] Step S501, interpreting the copywriting phrases to obtain the meaning of the phrases;

[0120] Step S502, based on the meaning of the phrases, the copywriting phrases are screened to obtain the target phrases;

[0121] Step S503: Based on the text evaluation index, the target phrase is tested for phrase normativity to obtain abnormal phrase information of the text.

[0122] In step S501 of some embodiments, the present application may utilize semantic recognition tools to interpret each copywriting phrase in the target copywriting data to determine the meaning of the copywriting phrase in a specific context, i.e., the phrase meaning. For example, in financial target copywriting data, the phrase meaning of the phrase "high-yield investment" may be an investment opportunity that promises high returns.

[0123] In step S502 of some embodiments, based on the phrase meanings of the above-mentioned copywriting phrases, the copywriting review system can filter out target phrases related to the copywriting evaluation indicators. For example, in the financial target copywriting data, if there are copywriting phrases such as "risk-free", "high-yield investment", and "guaranteed return", then target phrases such as "risk-free" and "guaranteed return" that violate the compliance requirements of financial advertisements may be filtered out.

[0124] In step S503 of some embodiments, the selected target phrases may be detected using the copy evaluation indicators to determine whether the target phrases meet the specifications and standards of the copy evaluation indicators, and then the detected abnormal target phrases may be summarized to form copy abnormal phrase information. For example, the target copy data of the financial category includes the target phrase "risk-free investment". According to the copy evaluation indicators of the financial industry, the target phrase will be regarded as an abnormal target phrase.

[0125] In steps S501 to S503 shown in this embodiment, the copy phrases in the target copy data are interpreted in detail to determine the meaning of the copy phrases, and then the target phrases related to the target copy data evaluation indicators are screened out based on the meaning of the phrases. Finally, the target phrases are subjected to a normative test to identify abnormal phrases that do not meet the financial industry standards or regulatory requirements, thereby obtaining copy abnormal phrase information, which can ensure the compliance and accuracy of the copy.

[0126] In step S405 of some embodiments, grammatical anomaly detection is to identify whether the text grammar in the target text data meets the text evaluation index.

[0127] The present application analyzes the copywriting phrases to determine the part of speech of each copywriting phrase, and then uses the part of speech to perform grammatical analysis on the entire target copywriting data to construct the grammatical structure of the target copywriting data. Finally, the grammatical structure is checked for standardization based on the copywriting evaluation indicators, thereby identifying abnormal grammatical structures that do not conform to language specifications or industry standards, and then abnormal grammatical information of the copywriting is generated based on the abnormal grammatical structures.

[0128] For details, see Figure 6 In some embodiments, step S405 may include but is not limited to steps S601 to S603:

[0129] Step S601, parsing the copywriting phrase to obtain the part of speech of the phrase;

[0130] Step S602, based on the word group part of speech, grammar analysis is performed on the target copy data to obtain the copy grammar;

[0131] Step S603: Based on the text evaluation index, the text grammar is checked for grammatical standardization to obtain abnormal text grammar information.

[0132] In step S601 of some embodiments, the text phrases can be parsed by natural language processing technology to determine the part-of-speech information of each text phrase, that is, the phrase part-of-speech. It should be noted that the phrase part-of-speech can be a noun, verb, adjective, etc.

[0133] In step S602 of some embodiments, the grammatical structure of the target text data may be parsed according to the above-mentioned phrase parts of speech, thereby generating a syntax tree of the target text data, and then performing syntax recognition on the syntax tree to obtain the text grammar of the target text data.

[0134] In step S603 of some embodiments, the copywriting evaluation index can be used to perform a grammatical structure normative detection on the copywriting grammar of the target copywriting data, so as to identify abnormal copywriting grammar in the target copywriting data. Furthermore, the detected abnormal copywriting grammar is summarized to obtain the abnormal copywriting grammar information.

[0135] In steps S601 to S603 shown in this embodiment, the copy phrases in the target copy data are parsed to determine the part of speech of each copy phrase, and then the whole target copy data is parsed using the part of speech to construct the grammatical structure of the target copy data. Finally, the copy grammar is checked for standardization based on the copy evaluation index, thereby identifying abnormal grammatical structures that do not meet the language specifications or industry standards in the copy evaluation index, obtaining abnormal grammatical information of the copy, and ensuring the grammatical accuracy and professionalism of the copy.

[0136] In step S406 of some embodiments, information merging is to integrate abnormal information of copy sentiment, copy phrases and copy grammar to form a comprehensive copy content abnormal information report.

[0137] This application can detect abnormal emotional information in the copywriting 、 Abnormal copywriting sentiment information and abnormal copywriting sentiment information are summarized to generate detailed abnormal copywriting content information. It should be noted that the abnormal copywriting content information can point out the areas that need to be modified in the target copywriting data and provide modification suggestions.

[0138] In steps S401 to S405 shown in this embodiment, sentiment analysis is used to identify the sentiment tendency in the target copy data, and then the appropriateness of the sentiment of the copy is evaluated based on the copy evaluation index. Then, the target copy data is segmented, the compliance of the copy phrases is identified and detected, and grammar detection is performed to ensure the grammatical correctness of the target copy data. Finally, the abnormal information of sentiment, phrases and grammar is merged to form a comprehensive copy content abnormal information report, thereby improving the accuracy of abnormal copy rewriting, ensuring that the copy meets the requirements of the copy evaluation index in terms of sentiment expression, word accuracy and grammatical standardization, and ensuring the quality and compliance of the copy.

[0139] In step S107 of some embodiments, the target copy data can be parsed by natural language processing technology to obtain the copy context information of the target copy data, and then the abnormal part of the target copy data can be accurately located by using the above copy content abnormal information, and finally the abnormal part can be modified in combination with the copy context information.

[0140] For details, see Figure 7 In some embodiments, step S107 may include but is not limited to steps S701 to S703:

[0141] Step S701, performing natural language processing on the target copy data to obtain copy context information;

[0142] Step S702, based on the abnormal information of the copy content, abnormal location is performed on the target copy data to obtain the abnormal information location;

[0143] Step S703, based on the copy context information, modify the copy at the abnormal information location to obtain a standard copy.

[0144] In step S701 of some embodiments, the copy review system can use mature natural language processing tools to perform entity recognition, relationship recognition and overall context recognition on the target copy data, and integrate and analyze the recognized copy to obtain copy context information, wherein the natural language processing tool can be a sentiment analyzer, a part-of-speech tagger and a syntactic analyzer.

[0145] In step S702 of some embodiments, based on the above-mentioned abnormal information of the copy content, the copy review system can determine the location where the copy abnormality occurs in the target copy data, that is, the abnormal information location, through information search.

[0146] In step S703 of some embodiments, after obtaining the location of the abnormal information, the copy review system can locate the abnormality in the target copy data, and then modify the abnormal part of the target copy data according to the copy context information and the copy evaluation indicators to obtain a modified copy. Furthermore, the copy review system can re-evaluate the modified copy until the modified copy meets the copy evaluation indicators to obtain a standard copy. For example, in financial target copy data, by modifying the "guaranteed high returns" in the target copy data to "expected high returns, but please pay attention to investment risks", the copy modification of the target copy data can be achieved to obtain a standard copy.

[0147] In an application scenario, taking financial product promotional copy as an example, first, the copy evaluation guide data of the financial industry is obtained, wherein the copy evaluation guide data includes industry norms, regulatory requirements and best practices; then, a preset financial product promotional copy is classified, such as identifying it as an "investment product" category, and then, based on the "investment product" category, a copy review instruction text is generated, wherein the copy review instruction text may emphasize the accuracy of risk disclosure and return forecasts that require special attention, and then, according to the copy review instruction text, specific copy evaluation indicators are extracted from the copy evaluation guide data, such as "avoiding the use of misleading statements" and "ensuring information transparency", and then, the copy evaluation indicators are used to perform anomaly detection on the target copy data to identify abnormal copy content information such as "guaranteed high returns" that may mislead consumers; finally, based on the detected abnormal copy content information, the target copy data is rewritten, and "guaranteed high returns" is changed to "expected high returns, but please pay attention to investment risks" to ensure the compliance and accuracy of the copy. This solution can improve the accuracy of product promotion copy review.

[0148] This application establishes the review standard of the copy by acquiring the copy evaluation guide data, then performs feature extraction on the preset target copy data to obtain the copy features, and classifies the target copy data according to the copy features to identify the field to which the target copy data belongs, then performs copy analysis on the copy features to obtain the basic copy information, and based on the copy category and the basic copy information, screens the preset review instruction template library to obtain the copy review instruction text, and provides targeted instructions for the copy review system, then extracts key copy evaluation indicators from the copy evaluation guide data, uses the copy evaluation indicators to perform anomaly detection on the target copy data, identifies non-compliant or inaccurate content, and finally, performs necessary rewriting on the copy based on the detection results to ensure its accuracy, compliance, clarity and appropriateness, thereby reducing the subjectivity of manual review and improving the accuracy of abnormal copy rewriting.

[0149] See also Figure 8The embodiment of the present application also provides an abnormal text rewriting device, which can implement the above abnormal text rewriting method, and the device includes:

[0150] Evaluation guide acquisition module 801, used to acquire copywriting evaluation guide data;

[0151] The document feature extraction module 802 is used to extract features from preset target document data to obtain document features;

[0152] The text category prediction module 803 is used to classify the target text data based on the text features to obtain the text category;

[0153] The instruction text generation module 804 is used to analyze the text features to obtain basic information of the text, and to screen the preset review instruction template library based on the text category and the basic information of the text to obtain the text review instruction text;

[0154] Evaluation index extraction module 805, used to extract information from the copy evaluation guide data based on the copy review instruction text to obtain the copy evaluation index;

[0155] The copy anomaly detection module 806 is used to perform copy content anomaly detection on the target copy data based on the copy evaluation index to obtain copy content anomaly information;

[0156] The abnormal copy rewriting module 807 is used to rewrite the target copy data based on the abnormal copy content information.

[0157] The specific implementation of the abnormal text rewriting device is basically the same as the specific implementation of the abnormal text rewriting method mentioned above, and will not be repeated here.

[0158] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above abnormal text rewriting method when executing the computer program. The electronic device can be any intelligent terminal including a tablet computer, a car computer, etc.

[0159] See also Fig. 9 , Fig. 9 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0160] The processor 901 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0161] The memory 902 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 902 can store an operating system and other applications. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 902, and the processor 901 calls and executes the abnormal text rewriting method of the embodiment of this application;

[0162] Input / output interface 903, used to implement information input and output;

[0163] Communication interface 904, used to realize communication interaction between the device and other devices, which can be realized by wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0164] A bus 905 that transmits information between various components of the device (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904);

[0165] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0166] 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, the above-mentioned abnormal text rewriting method is implemented.

[0167] 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 disposed 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.

[0168] The abnormal copy rewriting method, abnormal copy rewriting device, electronic device and storage medium provided in the embodiment of the present application are applied to the copy review system, which obtains copy evaluation guide data, then extracts features of preset target copy data to obtain copy features, and classifies the target copy data according to the copy features to obtain copy categories, further, performs copy analysis on the copy features to obtain copy basic information, and based on the copy categories and copy basic information, screens the preset review instruction template library to obtain the copy review instruction text, then extracts information from the copy evaluation guide data according to the copy review instruction text to obtain the copy evaluation index, and then performs copy content anomaly detection on the target copy data according to the copy evaluation index to obtain copy content anomaly information, and finally, performs copy rewriting on the target copy data according to the copy content anomaly information. .

[0169] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present 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 the present application are also applicable to similar technical problems.

[0170] Those skilled in the art will appreciate 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.

[0171] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0172] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0173] 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 sequence. 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 of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising 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.

[0174] It should be understood that in the present 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 objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single 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.

[0175] In the several embodiments provided in the present 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 only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. 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.

[0176] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0177] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0178] 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, and the computer software product is stored in a storage medium, including multiple instructions to enable 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: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0179] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for rewriting abnormal text, characterized in that: The method comprises: Get copywriting assessment guide data; Extract features from preset target copywriting data to obtain copywriting features; Classifying the target copy data based on the copy features to obtain a copy category; Performing a copy analysis on the copy features to obtain basic copy information, and screening a preset review instruction template library based on the copy category and the basic copy information to obtain a copy review instruction text; Based on the copy review instruction text, extract information from the copy evaluation guide data to obtain a copy evaluation index; Based on the copy evaluation index, the target copy data is subjected to copy content anomaly detection to obtain copy content anomaly information; Based on the abnormal content information of the copy, the target copy data is rewritten.

2. The method according to claim 1, characterized in that: The process of performing text content anomaly detection on the target text data based on the text evaluation index to obtain text content anomaly information includes: Performing sentiment analysis on the target copywriting data to obtain the copywriting sentiment; Based on the copy evaluation index, the copy emotion is evaluated to obtain abnormal copy emotion information; Performing word segmentation processing on the target copywriting data to obtain copywriting phrases; Based on the copy evaluation index, performing phrase anomaly detection on the copy phrase to obtain copy abnormal phrase information; Based on the copywriting phrases and the copywriting evaluation index, grammatical anomaly detection is performed on the target copywriting data to obtain copywriting abnormal grammatical information; The abnormal sentiment information of the copy, the abnormal phrase information of the copy and the abnormal grammatical information of the copy are merged to obtain the abnormal content information of the copy.

3. The method according to claim 2, characterized in that The step of performing phrase anomaly detection on the phrases in the copy based on the copy evaluation index to obtain abnormal phrase information in the copy includes: Performing phrase interpretation on the copywriting phrases to obtain the phrase meanings; Based on the meaning of the phrase, the copywriting phrase is screened to obtain a target phrase; Based on the text evaluation index, the target phrase is tested for phrase standardization to obtain the abnormal phrase information of the text.

4. The method according to claim 2, characterized in that: The step of performing grammatical anomaly detection on the target text data based on the text phrases and the text evaluation index to obtain text abnormal grammatical information includes: Performing phrase analysis on the copywriting phrase to obtain the phrase part of speech; Based on the word group part of speech, the target copywriting data is parsed to obtain the copywriting grammar; Based on the text evaluation index, the text grammar is checked for grammatical standardization to obtain abnormal grammatical information of the text.

5. The method according to claim 1, characterized in that The target copy data is classified based on the copy features to obtain a copy category, including: Performing feature mapping on the copy feature to obtain a feature category and a category confidence, wherein the category confidence is used to indicate the degree of credibility of the copy feature being the feature category; Based on the category confidence text feature, the feature category is selected to obtain the text category.

6. The method according to any one of claims 1 to 5, characterized in that: The step of extracting information from the copywriting evaluation guide data based on the copywriting review instruction text to obtain a copywriting evaluation index includes: Extracting audit information from the copy review instruction text to obtain key points for rewriting abnormal copy; Based on the abnormal copy rewriting key points, the copy evaluation guide data is screened to obtain the copy evaluation index.

7. The method according to any one of claims 1 to 5, characterized in that: The rewriting of the target copy data based on the copy content abnormal information includes: Performing natural language processing on the target copywriting data to obtain copywriting context information; Based on the abnormal information of the copy content, abnormal location is performed on the target copy data to obtain the abnormal information location; Based on the text context information, the text at the abnormal information location is modified to obtain a standard text.

8. An abnormal text rewriting device, characterized in that: The device comprises: Evaluation guide acquisition module, used to obtain copywriting evaluation guide data; The copy feature extraction module is used to extract features from preset target copy data to obtain copy features; A text category prediction module, used to classify the target text data based on the text features to obtain a text category; An instruction text generation module is used to perform text analysis on the text features to obtain basic information of the text, and to screen a preset review instruction template library based on the text category and the basic information of the text to obtain a text review instruction text; An evaluation index extraction module, used to extract information from the copywriting evaluation guide data based on the copywriting review instruction text to obtain a copywriting evaluation index; A copy anomaly detection module, used to perform copy content anomaly detection on the target copy data based on the copy evaluation index to obtain copy content anomaly information; The abnormal text rewriting module is used to rewrite the target text data based on the abnormal information of the text content.

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 abnormal text rewriting 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 abnormal text rewriting method according to any one of claims 1 to 7 is implemented.

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