Cboth information generation method and device and related equipment
By obtaining and processing product attribute data to generate attribute tags and entering material information models, the problems of low efficiency and homogeneity of traditional marketing material generation are solved, and accurate copy information generation is achieved, improving market response speed and user experience.
Patent Information
- Application Number
- CN202411081372.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-07
- Publication Date
- 2024-12-17
AI Technical Summary
When traditional manual methods deal with the generation of massive product attributes and corresponding marketing materials, they are inefficient and difficult to accurately match the needs of the target customer group, resulting in slow market response speed, discounted marketing effects, homogeneous and templated existing product materials. The product characteristics cannot be accurately reflected.
By obtaining the attribute data of the product or product, preprocessing is performed to obtain attribute tags, and inputting these tags into the pre-trained material information generation model to generate corresponding material information, and finally generating accurate copy information based on the material information.
It improves the attractiveness of copywriting information, reduces labor costs, enhances user experience, ensures that copywriting information can accurately reflect the characteristics of the product or product, and solves the problems of inefficiency and insufficient personalization.
Smart Images
Figure CN119149725A_ABST
Abstract
Description
Background Art
[0002] With the rapid development of information technology and increasingly fierce market competition, operators are facing unprecedented challenges and opportunities. In order to attract and retain customers, operators continue to launch a variety of product and service packages with a wide variety of products and services that are updated rapidly. However, traditional manual methods are not only inefficient in processing massive product attributes and generating corresponding marketing materials, but also difficult to accurately match the needs of target customer groups, resulting in slow market response and discounted marketing effects. Existing product materials are often highly homogenized and templated, lacking in specificity, and unable to accurately reflect product features, affecting user understanding and purchasing decisions.
[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention
[0004] The present disclosure provides a copywriting information generation method, device and related equipment, which at least to a certain extent overcome the problem that the marketing materials of goods or products in the related art are often highly homogenized and templated, lack specificity, and cannot generate marketing copywriting that accurately reflects the characteristics of goods or products.
[0005] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.
[0006] According to one aspect of the present disclosure, a method for generating copywriting information is provided, comprising: acquiring attribute data of a target object, wherein the target object is a commodity or a product; preprocessing the attribute data of the target object to obtain an attribute label of the target object, wherein the attribute label is feature information associated with material information corresponding to the target object; inputting the attribute label of the target object into a pre-trained material information generation model, and outputting material information corresponding to the attribute label; and generating copywriting information of the target object based on the material information corresponding to the attribute data of the target object.
[0007] In some exemplary embodiments of the present disclosure, based on the aforementioned scheme, the attribute data of the target object is preprocessed to obtain the attribute label of the target object, including: standardizing the attribute data of the target object to obtain standardized attribute information of the target object; and determining the attribute label corresponding to the keyword group based on the keyword group in the standardized attribute information.
[0008] In some exemplary embodiments of the present disclosure, based on the aforementioned scheme, the attribute label corresponding to the keyword group is determined according to the keyword group in the standardized attribute information, including: based on a pre-built attribute label mapping rule library, the attribute label corresponding to the keyword group is determined according to the keyword group of the target object.
[0009] In some exemplary embodiments of the present disclosure, based on the aforementioned scheme, before determining the attribute label corresponding to the keyword group according to the keyword group of the target object based on a pre-constructed attribute label mapping rule library, the method also includes: inputting the keyword group of the target object into a pre-trained attribute label and rule generation model, outputting the attribute label corresponding to the keyword group and the mapping rule corresponding to the attribute label; and constructing the attribute label mapping rule library according to the attribute label corresponding to the keyword group and the mapping rule corresponding to the attribute label.
[0010] In some exemplary embodiments of the present disclosure, based on the aforementioned solution, the method further includes: updating the attribute tags corresponding to the keyword groups and the mapping rules corresponding to the attribute tags to the attribute tag mapping rule library.
[0011] In some exemplary embodiments of the present disclosure, based on the aforementioned scheme, the attribute data of the target object includes: commodity or product information in the form of a picture. Before standardizing the attribute data of the target object to obtain the standardized attribute information of the target object, the method also includes: performing image recognition on the commodity or product information in the form of a picture to obtain the commodity or product information in text form.
[0012] In some exemplary embodiments of the present disclosure, based on the aforementioned scheme, the keyword group of the target object includes at least one of the following: product name, service type, functional characteristics, applicable area, price constraints, sales method, logistics information, and supplementary instructions.
[0013] According to another aspect of the present disclosure, there is also provided a copy information generation device, including: an attribute data acquisition module, used to acquire attribute data of a target object, wherein the target object is a commodity or product; an attribute data processing module, used to preprocess the attribute data of the target object to obtain an attribute label of the target object, wherein the attribute label is feature information associated with material information corresponding to the target object; a material information output module, used to input the attribute label of the target object into a pre-trained material information generation model, and output the material information corresponding to the attribute label; and a copy information generation module, used to generate the copy information of the target object based on the material information corresponding to the attribute data of the target object.
[0014] According to another aspect of the present disclosure, there is also provided an electronic device, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the above-mentioned copywriting information generation methods by executing the executable instructions.
[0015] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, any one of the above-mentioned methods for generating copywriting information is implemented.
[0016] According to another aspect of the present disclosure, a computer program product is provided, including: a computer program or instructions, wherein when the computer program or instructions are executed by a processor, any one of the above-mentioned methods for generating text information is implemented.
[0017] A copy information generation method, device and related equipment provided in the embodiments of the present disclosure determine the attribute tags corresponding to the target object, and input the attribute tags into the material information generation model to generate the material information corresponding to the target object, and finally generate more accurate copy information according to the material information of the target object, thereby solving the problems of slow speed, low efficiency and insufficient personalization of the copy information of the target object, that is, the commodity or product in the related technology. The material information generation model is used to generate copy information that more accurately reflects the characteristics of the target object, thereby improving the attractiveness of the copy information, reducing labor costs and enhancing user experience.
[0018] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.
[0020] Figure 1 A schematic diagram showing an exemplary application system architecture of a method for generating copywriting information in an embodiment of the present disclosure;
[0021] Figure 2 A schematic diagram of a method for generating copywriting information in an embodiment of the present disclosure is shown;
[0022] Figure 3 A schematic diagram of a method for determining an attribute label of a target object in an embodiment of the present disclosure is shown;
[0023] Figure 4A schematic diagram of a material information generation process in an embodiment of the present disclosure is shown;
[0024] Figure 5 A schematic diagram of a process for generating copywriting information of a product in an embodiment of the present disclosure is shown;
[0025] Figure 6 A schematic diagram of a copywriting information generating device in an embodiment of the present disclosure is shown;
[0026] Figure 7 A schematic diagram of an electronic device showing a method for generating application copy information in an embodiment of the present disclosure. DETAILED DESCRIPTION
[0027] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the disclosure will be more comprehensive and complete and to fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0028] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.
[0029] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.
[0030] Figure 1 FIG. 1 shows an exemplary application system architecture diagram to which the copywriting information generation method in the embodiment of the present disclosure can be applied. Figure 1 As shown, the system architecture may include a terminal device 101 , a network 102 and a server 103 .
[0031] The network 102 is a medium for providing a communication link between the terminal device 101 and the server 103, and can be a wired network or a wireless network.
[0032] Optionally, the wireless network or wired network described above uses standard communication technology and / or protocol. The network is usually the Internet, but it can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a dedicated network or any combination of a virtual private network). In some embodiments, technologies and / or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. are used to represent data exchanged through the network. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec) can also be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above data communication technologies.
[0033] The terminal device 101 can be various electronic devices, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, wearable devices, augmented reality devices, virtual reality devices, etc.
[0034] Optionally, the client of the application installed in different terminal devices 101 is the same, or the client of the same type of application based on different operating systems. Based on the different terminal platforms, the specific form of the client of the application can also be different, for example, the application client can be a mobile client, a PC client, etc.
[0035] The server 103 may be a server that provides various services, such as a background management server that provides support for the device operated by the user using the terminal device 301. The background management server may analyze and process the received request and other data, and feed back the processing results to the terminal device.
[0036] Optionally, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or 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 (Content Delivery Network), and big data and artificial intelligence platforms. The terminal can be a smart phone, tablet computer, laptop computer, desktop computer, smart speaker, smart watch, etc., but is not limited to this. The terminal and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in this application.
[0037] Those skilled in the art will know that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration, and any number of terminal devices, networks and servers may be provided according to actual needs, and the embodiments of the present disclosure do not limit this.
[0038] Under the above system architecture, a method for generating copywriting information is provided in an embodiment of the present disclosure. The method can be executed by any electronic device with computing and processing capabilities.
[0039] In some embodiments, the copywriting information generation method provided in the embodiments of the present disclosure can be executed by a terminal device of the above-mentioned system architecture; in other embodiments, the copywriting information generation method provided in the embodiments of the present disclosure can be executed by a server in the above-mentioned system architecture; in other embodiments, the copywriting information generation method provided in the embodiments of the present disclosure can be implemented by the terminal device and the server in the above-mentioned system architecture through interaction.
[0040] First of all, in response to the above-mentioned problems, a method for generating marketing copy information that can be applied to but is not limited to commodities or products is provided in the embodiments of the present disclosure. The method can be applied to any matter that requires the generation of material information to create marketing copy, for example, the investment promotion copy released by a marketing company is time-consuming and labor-intensive compared to the manual production of marketing materials in related technologies, and it is difficult to quickly respond to market changes. Moreover, existing materials are often highly homogenized and templated, lacking in specificity, and unable to accurately reflect product features, thus affecting user understanding and purchasing decisions. The embodiments of the present disclosure determine the attribute labels corresponding to the target object, and input the attribute labels into the material information generation model to generate the material information corresponding to the target object, and finally generate more accurate copy information based on the material information of the target object. Moreover, the material information generation model can quickly generate copy information that more accurately reflects the characteristics of the target object, thereby increasing the attractiveness of the copy information, reducing labor costs, and enhancing user experience.
[0041] Figure 2A schematic diagram of a method for generating copywriting information in an embodiment of the present disclosure is shown, and the method comprises the following steps:
[0042] S202, acquiring attribute data of a target object, wherein the target object is a commodity or a product.
[0043] It should be noted that the target object in the embodiments of the present disclosure may be a commodity or product launched by any merchant, for example, a package product launched by an operator, or a technology product launched by a technology company. More specifically, the attribute data of the target object in the embodiments of the present disclosure may be a textual overview of the commodity or product, or a picture overview of the commodity or product. For example, the attribute data of a package product launched by an operator includes the commodity name, service type, functional characteristics, applicable area, price constraints, sales method, logistics information, supplementary instructions, etc., which are introduced in pictures and texts.
[0044] S204, preprocessing the attribute data of the target object to obtain an attribute label of the target object, where the attribute label is feature information associated with the material information corresponding to the target object.
[0045] It should be noted that the preprocessing in the embodiments of the present disclosure may specifically include cleaning and standardizing the attribute data of the target object, removing invalid information, filling in missing values, unifying units and formats, and other processing operations; and, the attribute labels in the embodiments of the present disclosure express important features associated with the material information in the attribute data of the target object. For example, a 300G traffic package launched by an operator may have an attribute label of "high traffic".
[0046] S206, inputting the attribute label of the target object into a pre-trained material information generation model, and outputting the material information corresponding to the attribute label.
[0047] It should be noted that the material information generation model in the embodiment of the present disclosure can be a model obtained by pre-training various artificial intelligence algorithm models (for example, a neural network model) or their combination models through machine learning. The model can automatically identify the attribute labels of the target objects and match the material information corresponding to the attribute labels. The input data of the model is the attribute labels of the target objects, and the output data is the material information associated with the attribute labels.
[0048] S208: Generate text information of the target object based on the material information corresponding to the attribute data of the target object.
[0049] The copy information generation method provided in the embodiments of the present disclosure first obtains the attribute data of the target object; secondly, pre-processes the attribute data of the target object to obtain the attribute label of the target object; then, inputs the attribute label of the target object into a pre-trained material information generation model, and outputs the material information corresponding to the attribute label; finally, generates the copy information of the target object based on the material information corresponding to the attribute data of the target object. Compared with the related art in which the copy information of the target object is manually customized, there are problems of slow speed, low efficiency and insufficient personalization. The embodiments of the present disclosure determine the attribute label corresponding to the target object, and input the attribute label into the material information generation model to generate the material information corresponding to the target object. Finally, more accurate copy information is generated according to the material information of the target object, thereby improving the attractiveness of the copy information, reducing labor costs and enhancing user experience.
[0050] In some embodiments, Figure 3 As shown, in the embodiment of the present disclosure, the attribute data of the target object is preprocessed to obtain the attribute label of the target object, including:
[0051] S302, performing standardization processing on the attribute data of the target object to obtain standardized attribute information of the target object;
[0052] S304: Determine the attribute label corresponding to the keyword group according to the keyword group in the standardized attribute information.
[0053] In some embodiments, the embodiments of the present disclosure may define associated standardized attribute tags through the business needs and attribute information of the target object. Specifically, the embodiments of the present disclosure obtain standardized attribute information by preprocessing the attribute data of the target object so that a more standardized analysis of the target object can be performed subsequently through the standardized attribute information, thereby ensuring that more accurate copy information can be generated subsequently.
[0054] In some embodiments, the disclosed embodiments determine the attribute label corresponding to the keyword group according to the keyword group in the standardized attribute information, including: based on a pre-built attribute label mapping rule base, according to the keyword group of the target object, determine the attribute label corresponding to the keyword group. Specifically, if the target object in the disclosed embodiments is a traffic package launched by a certain operator, the keyword group of the target object may be "traffic", "user", "rights", etc. According to the keyword group of the target object, the disclosed embodiments may also determine that the corresponding attribute label may be "high traffic", "family sharing", "exclusive for new users", "video rights", etc.
[0055] In some embodiments, before the present disclosure embodiment determines the attribute label corresponding to the keyword group according to the keyword group of the target object based on the pre-constructed attribute label mapping rule library, the copywriting information generation method in the present disclosure embodiment also includes: inputting the keyword group of the target object into a pre-trained attribute label and rule generation model, outputting the attribute label corresponding to the keyword group and the mapping rule corresponding to the attribute label; constructing an attribute label mapping rule library according to the attribute label corresponding to the keyword group and the mapping rule corresponding to the attribute label. Specifically, the present disclosure embodiment generates attribute labels corresponding to the keyword group and the mapping rules corresponding to the attribute labels through the attribute label and rule generation model, wherein the attribute labels express the important features associated with the material information in the attribute data of the target object, and are used as the core prompt word input for the large model to generate the commodity material, and the mapping rules corresponding to the attribute labels can output the relevant attribute labels according to the input attribute data of the target object, and the user can also manually adjust the attribute label input according to actual needs.
[0056] In some embodiments, the copywriting information generation method in the disclosed embodiments further includes: updating the attribute tags corresponding to the keyword groups and the mapping rules corresponding to the attribute tags to the attribute tag mapping rule library. Specifically, when the attribute data of commodities or products is processed using the attribute tag and rule generation model, new attribute tags can also be extracted, and corresponding mapping rules can be generated and added to the attribute tag mapping rule library, thereby achieving more accurate material information for the target object.
[0057] In some embodiments, before the material information generation model is trained, the embodiments of the present disclosure also include: using cross-validation, AUC-ROC (Area Under Curve, defined as the area under the receiver operating characteristic curve and the coordinate axis) curve, accuracy, recall rate and other evaluation indicators to test the model performance, and iteratively optimize according to the actual application effect. For complex attributes that cannot be accurately extracted, the embodiments of the present disclosure will also introduce knowledge graphs to assist reasoning, or build more complex hybrid models, and finally complete and train the material information generation model required by the embodiments of the present disclosure.
[0058] In some embodiments, Figure 4 The material information generation process of the embodiment of the present disclosure specifically includes the following steps:
[0059] S402, if the material information generation model has not been trained, the attribute data of the target object is input into the attribute label mapping rule library; if the material information generation model has been trained in advance, the attribute data of the target object is directly input into the material information generation model, and the material information generation model outputs the corresponding material information;
[0060] S404, mapping the attribute labels corresponding to the attribute data of the target object through the attribute label mapping rule library, or supplementing the attribute labels corresponding to the attribute data of the target object by manual input;
[0061] S406, updating the newly added attribute tags and the mapping rules corresponding to the attribute tags to the attribute tag mapping rule library;
[0062] S408: Input the attribute label of the target object into the material information generation model, and output the material information corresponding to the attribute label.
[0063] In some embodiments, the attribute data of the target object in the disclosed embodiment includes: commodity or product information in the form of a picture. Before the attribute data of the target object is standardized to obtain the standardized attribute information of the target object, the copywriting information generation method in the disclosed embodiment also includes: performing image recognition on the commodity or product information in the form of a picture to obtain the commodity or product information in the form of text. Specifically, the disclosed embodiment can also use technologies such as image recognition and natural language processing to convert the commodity or product information in the form of a picture into the commodity or product information in the form of text, so as to facilitate the subsequent preprocessing of the attribute data of the target object, thereby obtaining the attribute label of the target object.
[0064] In some embodiments, the keyword group of the target object in the embodiments of the present disclosure includes at least one of the following: product name, service type, functional characteristics, applicable area, price constraints, sales method, logistics information, and supplementary instructions.
[0065] In some embodiments, Figure 5 As shown, the embodiment of the present disclosure uses the above-mentioned copy information generation method to generate corresponding copy information for the selected product. The specific process includes the following steps:
[0066] S502, obtaining attribute data of the selected commodity.
[0067] In some embodiments, the embodiments of the present disclosure assume that the selected product is a "5G large-traffic family package" launched by a certain operator. The attribute data of the product may include: product overview, graphic introduction, product name, service type, functional characteristics, applicable area, price constraints, sales method, logistics information, supplementary instructions, etc.
[0068] S504, clean and standardize the attribute data of the selected commodities, remove invalid information, fill in missing values, and unify units and formats.
[0069] In some embodiments, the attribute data processed by the embodiments of the present disclosure may be as follows:
[0070] 1) Product name: 5G large data traffic family package;
[0071] 2) Service type: mobile communication service;
[0072] 3) Features: 5G high-speed Internet access, 500G data traffic, multi-device sharing, and free calls between family members;
[0073] 4) Applicable area: unlimited nationwide;
[0074] 5) Price constraints: monthly fee of 299 yuan, contract period of 2 years;
[0075] 6) Sales method: order online, purchase in physical stores;
[0076] 7) Logistics information: electronic card code is sent immediately;
[0077] 8) Additional information: 100GB of cloud storage space is included, and the first month is free for trial.
[0078] In some embodiments, the disclosed embodiments cleanse and standardize the attribute data of the selected commodities so that subsequent analysis and modeling can be performed based on the processed attribute data.
[0079] S506, determining a keyword group from the attribute data of the selected commodity according to business understanding, and determining an attribute label corresponding to the keyword group.
[0080] In some embodiments, the embodiments of the present disclosure construct an attribute label mapping rule base based on the common characteristics and market positioning of the operator's products, wherein the construction of the attribute label mapping rule base is specifically as follows:
[0081] 1) Traffic type: If it contains "5G" and "traffic > 300G", the label will be "5G Premium" or "High Traffic Enjoyment";
[0082] 2) Applicable groups: "Family Package" is labeled "Family Sharing";
[0083] 3) Price advantage: If the monthly fee is less than 300 yuan, the label is "economical";
[0084] 4) Additional benefits: “Free calls” and “cloud storage” are labeled as “family connections” and “cloud convenience”.
[0085] By constructing a good attribute label mapping rule library, the attribute information after processing of the above-mentioned "5G large-traffic family package" is determined, and the corresponding attribute labels are "5G exclusive", "large-traffic enjoyment", "family sharing", "economical and affordable", "family connection", and "cloud convenience".
[0086] S508: Input the attribute label of the selected product into a pre-trained material information generation model, and output the material information corresponding to the attribute label.
[0087] In more detail, the product copy information generated by the embodiment of the present disclosure may be:
[0088] "Connecting the future starts at home! We are proud to launch the new '5G Large Data Family Package', designed for you who pursue speed and unlimited possibilities. Embrace the 5G exclusive network, whether it is HD video or online games, smooth experience, refuse to wait, and make every moment wonderful.
[0089] Family sharing, unlimited love! All the mobile phones, tablets, and computers of the whole family are covered in one network, and family members can enjoy free calls between each other, so that they can be connected emotionally at all times no matter where they are. The economical price is only 299 yuan per month, which is stable and worry-free during the contract period. It is a cost-effective choice and can be purchased online and offline, so you can easily own the future life.
[0090] Convenient cloud storage, worry-free storage! We have also prepared 100GB of cloud storage space for you, so that you can back up your precious memories and important files at any time and share them at will. The first month is free to try, full of sincerity, so that you can choose without any worries.
[0091] Take action now and start your family's 5G exclusive journey. Let us witness every advancement brought by technology and make life better with unlimited data!"
[0092] In some embodiments, the embodiments of the present disclosure combine technologies such as deep learning, natural language processing and image recognition to achieve automatic customization of visual and copywriting materials for the target object, that is, the selected goods or products. This not only improves the efficiency of material generation, but also ensures the diversity and creativity of the output material information through an in-depth understanding of the complex relationship between the attribute data of the goods or products and the material information through the material information generation model. Compared with the traditional method that relies on manual operation, the copywriting information generation method used in the embodiments of the present disclosure can automatically generate material information corresponding to the target object, and produce copywriting information for the target object, which not only speeds up market response and shortens the product customization cycle, but also reduces labor costs and generates copywriting information that more accurately reflects the characteristics of the target object.
[0093] In some embodiments, the disclosed embodiments can dynamically analyze the attribute data of the target object through an intelligently constructed attribute label mapping rule library, accurately fit the characteristics of each commodity or product, and generate highly personalized copy information. This mechanism not only overcomes the problem of material homogeneity, but also makes the copy information more closely aligned with the specific needs of the target object, thereby enhancing the user's willingness to buy. In addition, the disclosed embodiments can also manually adjust or automatically generate a new attribute label mapping rule library based on market feedback and business development, thereby ensuring the real-time and adaptability of the copy information strategy and further improving user experience and marketing efficiency.
[0094] Based on the same inventive concept, the present disclosure also provides a copy information generation device, such as the following embodiment. Since the principle of solving the problem in the device embodiment is similar to that in the above method embodiment, the implementation of the device embodiment can refer to the implementation of the above method embodiment, and the repeated parts will not be repeated.
[0095] Figure 6 A schematic diagram of a copywriting information generating device in an embodiment of the present disclosure is shown, and the device includes:
[0096] The attribute data acquisition module 601 is used to acquire the attribute data of the target object, wherein the target object is a commodity or a product;
[0097] The attribute data processing module 602 is used to pre-process the attribute data of the target object to obtain an attribute label of the target object, where the attribute label is feature information associated with the material information corresponding to the target object;
[0098] The material information output module 603 is used to input the attribute label of the target object into the pre-trained material information generation model, and output the material information corresponding to the attribute label;
[0099] The text information generating module 604 is used to generate text information of the target object based on the material information corresponding to the attribute data of the target object.
[0100] A copy information generation device provided in an embodiment of the present disclosure obtains the attribute data of a target object through an attribute data acquisition module; pre-processes the attribute data of the target object through an attribute data processing module to obtain the attribute label of the target object; inputs the attribute label of the target object into a pre-trained material information generation model through a material information output module, and outputs the material information corresponding to the attribute label; generates the copy information of the target object based on the material information corresponding to the attribute data of the target object through the copy information generation module. Compared with the related art in which the copy information of the target object is manually customized, there are problems of slow speed, low efficiency and insufficient personalization. The embodiment of the present disclosure determines the attribute label corresponding to the target object, and inputs the attribute label into the material information generation model to generate the material information corresponding to the target object, and finally generates more accurate copy information according to the material information of the target object, thereby improving the attractiveness of the copy information, reducing labor costs and enhancing user experience.
[0101] In some embodiments, the attribute data processing module in the disclosed embodiments is also used to standardize the attribute data of the target object to obtain standardized attribute information of the target object; and determine the attribute label corresponding to the keyword group according to the keyword group in the standardized attribute information.
[0102] In some embodiments, the attribute data processing module in the disclosed embodiments also determines the attribute label corresponding to the keyword group according to the keyword group of the target object based on a pre-built attribute label mapping rule library.
[0103] In some embodiments, the copywriting information generation device in the embodiments of the present disclosure further includes: a mapping rule output module, which is used to input the keyword group of the target object into a pre-trained attribute label and rule generation model before determining the attribute label corresponding to the keyword group according to the keyword group of the target object based on a pre-constructed attribute label mapping rule library, and output the attribute label corresponding to the keyword group and the mapping rule corresponding to the attribute label; an attribute label mapping rule library construction module, which is used to construct an attribute label mapping rule library according to the attribute label corresponding to the keyword group and the mapping rule corresponding to the attribute label.
[0104] In some embodiments, the copywriting information generating device in the embodiments of the present disclosure further includes: an attribute label mapping rule library updating module, which is used to update the attribute labels corresponding to the keyword groups and the mapping rules corresponding to the attribute labels to the attribute label mapping rule library.
[0105] In some embodiments, the attribute data of the target object in the embodiments of the present disclosure include: commodity or product information in the form of pictures, wherein the text information generation device in the embodiments of the present disclosure also includes: a picture-text conversion module, which is used to perform image recognition on the commodity or product information in the form of pictures before standardizing the attribute data of the target object to obtain the standardized attribute information of the target object, so as to obtain the commodity or product information in the form of text.
[0106] In some embodiments, the keyword group of the target object in the embodiments of the present disclosure includes at least one of the following: product name, service type, functional characteristics, applicable area, price constraints, sales method, logistics information, and supplementary instructions.
[0107] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods or program products. Therefore, various aspects of the present disclosure may be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as "circuits", "modules" or "systems".
[0108] Based on the same inventive concept, an electronic device is also provided in an embodiment of the present disclosure, the electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the above-mentioned methods for generating text information by executing the executable instructions. Since the principle of solving the problem in the electronic device embodiment is similar to that in the above-mentioned method embodiment, the implementation of the electronic device embodiment can refer to the implementation of the above-mentioned method embodiment, and the repeated parts will not be repeated.
[0109] Refer to the following Figure 7 An electronic device 700 according to this embodiment of the present disclosure is described. Figure 7 The electronic device 700 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.
[0110] like Figure 7 As shown, the electronic device 700 is in the form of a general computing device. The components of the electronic device 700 may include but are not limited to: at least one processing unit 701, at least one storage unit 702, and a bus 703 connecting different system components (including the storage unit 702 and the processing unit 701).
[0111] The storage unit stores program codes, which can be executed by the processing unit 701, so that the processing unit 701 executes the steps described in the above “exemplary method” section of this specification according to various exemplary embodiments of the present disclosure.
[0112] In some embodiments, when the electronic device is used to control the copywriting information generation method disclosed above, for example, the processing unit 701 may perform the following steps of the above method embodiment:
[0113] Acquire attribute data of a target object, wherein the target object is a commodity or a product; preprocess the attribute data of the target object to obtain an attribute label of the target object, wherein the attribute label is feature information associated with material information corresponding to the target object; input the attribute label of the target object into a pre-trained material information generation model, and output material information corresponding to the attribute label; generate text information of the target object based on the material information corresponding to the attribute data of the target object.
[0114] The storage unit 702 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 7021 and / or a cache storage unit 7022 , and may further include a read-only storage unit (ROM) 7023 .
[0115] The storage unit 702 may also include a program / utility 7024 having a set (at least one) of program modules 7025, such program modules 7025 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.
[0116] Bus 703 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.
[0117] The electronic device 700 may also communicate with one or more external devices 704 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 700, and / or may communicate with any device that enables the electronic device 700 to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface 705. In addition, the electronic device 700 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 706. As shown, the network adapter 706 communicates with other modules of the electronic device 700 through a bus 703. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.
[0118] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.
[0119] Based on the same inventive concept, the embodiment of the present disclosure also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, any of the above-mentioned methods for generating copywriting information is implemented. Since the principle of solving the problem in the embodiment of the computer-readable storage medium is similar to that in the above-mentioned method embodiment, the implementation of the embodiment of the computer-readable storage medium can refer to the implementation of the above-mentioned method embodiment, and the repeated parts will not be repeated.
[0120] More specific examples of computer-readable storage media in the present disclosure may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0121] In the present disclosure, a computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, wherein a readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A readable signal medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.
[0122] Alternatively, the program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.
[0123] In a specific implementation, the program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).
[0124] Based on the same inventive concept, a computer program product is also provided in the embodiments of the present disclosure, including a computer program product, including: a computer program or an instruction, and when the computer program or the instruction is executed by a processor, the method for generating text information in any one of the above method embodiments is implemented. Since the principle of solving the problem in the computer program product embodiment is similar to that in the above method embodiment, the implementation of the computer program product embodiment can refer to the implementation of the above method embodiment, and the repeated parts will not be repeated.
[0125] It should be noted that, although several modules or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be embodied.
[0126] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.
[0127] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the implementation of the present disclosure.
[0128] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the appended claims.
Claims
1. A method for generating copywriting information, characterized in that: include: Acquire attribute data of a target object, wherein the target object is a commodity or a product; Preprocessing the attribute data of the target object to obtain an attribute label of the target object, wherein the attribute label is feature information associated with material information corresponding to the target object; Inputting the attribute label of the target object into a pre-trained material information generation model, and outputting the material information corresponding to the attribute label; The text information of the target object is generated based on the material information corresponding to the attribute data of the target object.
2. The method for generating copywriting information according to claim 1, characterized in that: Preprocessing the attribute data of the target object to obtain the attribute label of the target object includes: Performing standardization processing on the attribute data of the target object to obtain standardized attribute information of the target object; According to the keyword group in the standardized attribute information, an attribute label corresponding to the keyword group is determined.
3. The method for generating copywriting information according to claim 2, characterized in that: Determining attribute labels corresponding to the keyword groups according to the standardized attribute information includes: Based on a pre-constructed attribute label mapping rule library, an attribute label corresponding to the keyword group is determined according to the keyword group of the target object.
4. The method for generating copywriting information according to claim 3, characterized in that: Before determining the attribute label corresponding to the keyword group according to the keyword group of the target object based on the pre-built attribute label mapping rule library, the method further includes: Inputting the keyword group of the target object into a pre-trained attribute label and rule generation model, and outputting the attribute label corresponding to the keyword group and the mapping rule corresponding to the attribute label; The attribute label mapping rule library is constructed according to the attribute labels corresponding to the keyword groups and the mapping rules corresponding to the attribute labels.
5. The method for generating copywriting information according to claim 4, characterized in that: The method further comprises: The attribute tags corresponding to the keyword groups and the mapping rules corresponding to the attribute tags are updated to the attribute tag mapping rule library.
6. The method for generating copywriting information according to claim 2, characterized in that: The attribute data of the target object includes: commodity or product information in the form of pictures. Before the attribute data of the target object is standardized to obtain the standardized attribute information of the target object, the method further includes: Image recognition is performed on the commodity or product information in the form of pictures to obtain the commodity or product information in the form of text.
7. The method for generating copywriting information according to claim 1, characterized in that: The keyword group of the target object includes at least one of the following: product name, service type, functional characteristics, applicable area, price constraint, sales method, logistics information, and supplementary instructions.
8. A copywriting information generating device, characterized in that: include: An attribute data acquisition module, used to acquire attribute data of a target object, wherein the target object is a commodity or a product; An attribute data processing module, used to pre-process the attribute data of the target object to obtain an attribute label of the target object, wherein the attribute label is feature information associated with the material information corresponding to the target object; A material information output module, used to input the attribute label of the target object into a pre-trained material information generation model, and output the material information corresponding to the attribute label; The copy information generation module is used to generate the copy information of the target object based on the material information corresponding to the attribute data of the target object.
9. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; The processor is configured to execute the method for generating text information according to any one of claims 1 to 7 by executing the executable instructions.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for generating text information according to any one of claims 1 to 7 is implemented.
11. A computer program product comprising: A computer program or instruction, characterized in that when the computer program or instruction is executed by a processor, it implements the copywriting information generation method described in any one of claims 1 to 7.