Automatic public domain-to-private domain guest obtaining system and method based on large model
Through the automated public domain to private domain customer acquisition system based on large models, the problems of long customer acquisition cycle and high cost in the existing customer acquisition methods are solved, and the effect of rapidly expanding customer scope and reducing costs is achieved.
Patent Information
- Application Number
- CN202411809858.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-10
- Publication Date
- 2025-04-25
Smart Images
Figure CN119887256A_ABST
Abstract
Description
Background Art
[0002] At present, most customer acquisition methods basically adopt the following method: first, obtain the behavior data of target users on the public domain platform; second, find potential users based on the behavior data of target users; then push information based on the behavior data of potential users; finally, when the potential users click or scan the pushed information, guide the potential users to jump from the public domain platform to the private domain platform. However, this method has two problems: first, the customer acquisition cycle is long; second, the manpower / capital cost is high. Summary of the invention
[0003] The present application provides a large-model-based automated public-domain-to-private-domain customer acquisition system and method, which is used to acquire customers through the public domain, expand the customer scope and quantity, and reduce costs.
[0004] First, a large-scale model-based automated public-domain to private-domain customer acquisition system is provided, including:
[0005] The big model automatic comment module is used to reply to the input comments based on the big model according to the popular comment data, and obtain customers who are interested in the reply content and send private messages;
[0006] The customer public domain to private domain module is used to convert the public domain to the private domain for the customers who are interested in the reply content and send private messages.
[0007] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved.
[0008] In a specific embodiment, it also includes:
[0009] The track screening module is used to screen the content of active tracks of potential customers and obtain the active track content.
[0010] In a specific embodiment, it also includes:
[0011] The popular video screening module is used to screen the popular videos in the active track content to obtain popular video data.
[0012] In a specific embodiment, it also includes:
[0013] The hot post screening module is used to extract the hot comments of the hot video data to obtain the hot comment data.
[0014] In a second aspect, a method for acquiring customers by automatically converting public domains to private domains based on a large model is provided, comprising the following steps:
[0015] Using the big model automatic comment module, based on the popular comment data, the input comments are replied based on the big model to obtain customers who are interested in the reply content and send private messages;
[0016] The customer public domain to private domain module is used to convert the public domain to the private domain for the customers who are interested in the reply content and send private messages.
[0017] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved.
[0018] In a specific embodiment, it also includes:
[0019] Use the track screening module to screen the content of potential customers' active tracks and obtain the active track content.
[0020] In a specific embodiment, it also includes:
[0021] The popular video screening module is used to screen the popular videos in the active track content to obtain popular video data.
[0022] In a specific embodiment, it also includes:
[0023] The hot post screening module is used to extract the hot comments of the hot video data to obtain the hot comment data.
[0024] In a third aspect, an electronic device is provided, comprising a processor, wherein the processor is coupled to a memory, wherein at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor so that the electronic device can implement any one of the large-model-based automated public-domain to private-domain customer acquisition methods.
[0025] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved.
[0026] In a fourth aspect, a computer-readable storage medium is provided, characterized in that at least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by a processor so that the computer-readable storage medium can implement any one of the large-model-based automated public-domain to private-domain customer acquisition methods.
[0027] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0028] Figure 1 A structural block diagram of an automated public-domain to private-domain customer acquisition system based on a large model provided in an embodiment of the present application;
[0029] Figure 2 A flowchart of a method for acquiring customers from a public domain to a private domain based on a large model provided in an embodiment of the present application;
[0030] Figure 3 A specific flow chart of the large-model-based automated public-domain to private-domain customer acquisition method provided in an embodiment of the present application. DETAILED DESCRIPTION
[0031] The present application is further described in detail below through the accompanying drawings and embodiments. Through these descriptions, the characteristics and advantages of the present application will become clearer and more specific.
[0032] The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. Although various aspects of the embodiments are shown in the drawings, the drawings are not necessarily drawn to scale unless otherwise noted.
[0033] In addition, the technical features involved in different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.
[0034] To facilitate understanding of the customer acquisition system and method for converting public domain to private domain based on a large model provided in the embodiment of the present application, its application scenario is first explained. The customer acquisition system and method for converting public domain to private domain based on a large model provided in the embodiment of the present application are used to acquire customers through the public domain, expand the scope and number of customers, and reduce costs. At present, most customer acquisition methods basically adopt the following method: first, obtain the behavior data of the target user on the public domain platform; second, find the intended user based on the behavior data of the target user; then push information based on the behavior data of the intended user; finally, when the intended user clicks or scans the push information, guide the intended user to jump from the public domain platform to the private domain platform. However, this method has two problems: first, the customer acquisition cycle is long; second, the manpower / capital cost is high. For this reason, the embodiment of the present application provides a customer acquisition system and method for converting public domain to private domain based on a large model, so as to acquire customers through the public domain, expand the scope and number of customers, and reduce costs. The following is a detailed description of the embodiment in conjunction with specific drawings.
[0035] refer to Figures 1 to 3 , Figure 1 A structural block diagram of an automated public-domain to private-domain customer acquisition system based on a large model provided in an embodiment of the present application; Figure 2 A flowchart of a method for acquiring customers from a public domain to a private domain based on a large model provided in an embodiment of the present application; Figure 3 A specific flow chart of the large-model-based automated public-domain to private-domain customer acquisition method provided in an embodiment of the present application.
[0036] exist Figure 1 In the embodiment of the present application, a customer acquisition system for automatically converting public domain to private domain based on a large model is provided, including:
[0037] The big model automatic comment module is used to reply to the input comments based on the big model according to the popular comment data, and obtain customers who are interested in the reply content and send private messages;
[0038] The customer public domain to private domain module is used to convert the public domain to the private domain for the customers who are interested in the reply content and send private messages.
[0039] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved.
[0040] In a specific embodiment, it also includes:
[0041] The track screening module is used to screen the content of active tracks of potential customers and obtain the active track content.
[0042] In a specific embodiment, it also includes:
[0043] The popular video screening module is used to screen the popular videos in the active track content to obtain popular video data.
[0044] In a specific embodiment, it also includes:
[0045] The hot post screening module is used to extract the hot comments of the hot video data to obtain the hot comment data.
[0046] exist Figure 2 In the embodiment of the present application, there is provided a method for acquiring customers by automatically converting public domains to private domains based on a large model, comprising the following steps:
[0047] Using the big model automatic comment module, based on the popular comment data, the input comments are replied based on the big model to obtain customers who are interested in the reply content and send private messages;
[0048] The customer public domain to private domain module is used to convert the public domain to the private domain for the customers who are interested in the reply content and send private messages.
[0049] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved.
[0050] In a specific embodiment, it also includes:
[0051] Use the track screening module to screen the content of potential customers' active tracks and obtain the active track content.
[0052] In a specific embodiment, it also includes:
[0053] The popular video screening module is used to screen the popular videos in the active track content to obtain popular video data.
[0054] In a specific embodiment, it also includes:
[0055] The hot post screening module is used to extract the hot comments of the hot video data to obtain the hot comment data.
[0056] Specifically, refer to Figure 3 The method for acquiring customers by automatically transferring from public domain to private domain based on a large model is a method for acquiring customers by automatically transferring from public domain to private domain based on a multimodal large model, and the specific steps are as follows:
[0057] S1 track screening module: first send a request to the self-media platform to establish a connection, then classify all video / graphic content into tracks, find the active track of potential customers, and filter out all content in the track.
[0058] S2 popular video screening module: extract all videos / pictures and texts in the track, screen videos / pictures and texts with more likes (number of collections) than the set value, sort by release time, screen popular content released in the past m days, and set the number of content items to the first n popular content items.
[0059] S3 hot post screening module: extract all comments in popular videos / pictures and texts, screen comments with more than t likes, sort by release time, and screen comments released within the last w days.
[0060] S4 large model automatic comment module: the filtered comments are input into the large model in batches, and the large model replies to the input comments according to the prompts and returns the replies to the self-media platform.
[0061] S5 customer public domain to private domain module: customers who are interested in the reply content and send private messages are guided to the WeChat end through speech skills, thus completing the conversion from public domain to private domain.
[0062] In this embodiment, the large model adopts a multimodal large language model.
[0063] Specifically, the Multimodal Large Language Model (MLLM) is a technology that combines vision and large language models.
[0064] The multimodal large language model can perceive inputs of different modes such as pictures and texts, and learn the context and generate answers in an autoregressive manner based on the instructions given by humans. It relies on the rich knowledge reserve and strong reasoning and generalization capabilities of the large language model (LLM) to solve multimodal problems, such as writing with pictures and writing code with pictures. The multimodal large language model uses technologies such as natural language processing, computer vision, and speech recognition, and integrates them into a system, so that it can understand human language and emotions more accurately.
[0065] A typical multimodal large language model can be abstracted into three modules, namely the pre-trained modality encoder, the pre-trained large language model (LLM), and the modality interface connecting them. Analogously to humans, modality encoders such as image / audio encoders are like human eyes / ears that receive and pre-process optical / acoustic signals, while LLMs are like human brains that understand and reason about the processed signals. In between, the modality interface is used to align different modalities. Some MLLMs also include a generator to output other modalities besides text.
[0066] Modality Encoder: An encoder compresses raw information, such as images or audio, into a more compact representation. Instead of training from scratch, a common approach is to use a pre-trained encoder that has been aligned with the other modality.
[0067] Pre-trained LLM: Instead of training an LLM from scratch, a more efficient and practical approach is to start from a pre-trained model. By pre-training on a large number of web corpora, LLMs have embedded rich world knowledge and demonstrated strong generalization and reasoning capabilities.
[0068] The training of a large multimodal language model usually includes two stages: multimodal pre-training and multimodal instruction tuning.
[0069] Multimodal pre-training: Using the X-Text dataset, we train the input and output projectors by optimizing predefined objectives to achieve alignment between various modalities.
[0070] Multimodal Instruction Fine-tuning: A method for fine-tuning pre-trained multimodal large language models using instruction-formatted datasets. Through this process, the model can generalize to unseen tasks by following new instructions, thereby improving zero-shot performance.
[0071] Advantages include: Multimodal Contextual Learning (M-ICL): An effective technique commonly used in the inference phase to improve few-shot performance.
[0072] Multimodal Chained Reasoning (M-CoT): Usually used for complex reasoning tasks.
[0073] LLM-based Visual Reasoning (LAVR): for joint reasoning tasks across visual and language modalities.
[0074] The multimodal large language model makes the system more intelligent and humane by integrating information from multiple modalities such as text, voice, and images.
[0075] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved.
[0076] An embodiment of the present application also provides an electronic device, comprising a processor, wherein the processor is coupled to a memory, wherein at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor, so that the electronic device can implement any one of the large-model-based automated public-domain to private-domain customer acquisition methods.
[0077] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved.
[0078] An embodiment of the present application also provides a computer-readable storage medium, characterized in that at least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by a processor so that the computer-readable storage medium can implement any one of the large-model-based automated public-domain to private-domain customer acquisition methods.
[0079] In the above technical solution, a large model automatic comment module is used to reply to input comments based on a large model according to popular comment data, and obtain customers who are interested in the reply content and send private messages; a customer public domain to private domain module is used to convert the customers who are interested in the reply content and send private messages from public domain to private domain; by acquiring customers in the public domain, the customer range and number are expanded; costs are saved, time and effort are saved, and efficiency is greatly improved.
[0080] Those skilled in the art will appreciate that the present application may be implemented as a system, method or computer program product.
[0081] Therefore, the present disclosure may be specifically implemented in the following forms, namely: it may be completely hardware, it may be completely software (including firmware, resident software, microcode, etc.), or it may be a combination of hardware and software, generally referred to herein as a "circuit", "module" or "system". In addition, in some embodiments, the present application may also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium may contain computer-readable program code.
[0082] Any combination of one or more computer-readable media can be used. Computer-readable media can be computer-readable signal media or computer-readable storage media. Computer-readable storage media can be, for example, but not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or devices, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, computer-readable storage media can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.
[0083] Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art can change, modify, replace and modify the above embodiments within the scope of the present application. On this basis, a variety of replacements and improvements can be made to the present application, all of which fall within the scope of protection of the present application.
Claims
1. An automated public-domain to private-domain customer acquisition system based on a large model, characterized in that: include: The big model automatic comment module is used to reply to the input comments based on the big model according to the popular comment data, and obtain customers who are interested in the reply content and send private messages; The customer public domain to private domain module is used to convert the public domain to the private domain for the customers who are interested in the reply content and send private messages.
2. The large-model-based automated public-domain-to-private-domain customer acquisition system according to claim 1 is characterized in that: Also includes: The track screening module is used to screen the content of active tracks of potential customers and obtain the active track content.
3. The large-model-based automated public-domain-to-private-domain customer acquisition system according to claim 2 is characterized in that: Also includes: The popular video screening module is used to screen the popular videos in the active track content to obtain popular video data.
4. The large-model-based automated public-domain-to-private-domain customer acquisition system according to claim 3 is characterized in that: Also includes: The hot post screening module is used to extract the hot comments of the hot video data to obtain the hot comment data.
5. A method for acquiring customers by automatically converting public domains to private domains based on a large model, characterized in that: The following steps are involved: Using the big model automatic comment module, based on the popular comment data, the input comments are replied based on the big model to obtain customers who are interested in the reply content and send private messages; The customer public domain to private domain module is used to convert the public domain to the private domain for the customers who are interested in the reply content and send private messages.
6. The method for acquiring customers from public domain to private domain based on a large model according to claim 5, characterized in that: Also includes: Use the track screening module to screen the content of potential customers' active tracks and obtain the active track content.
7. The method for acquiring customers from public domain to private domain based on a large model according to claim 6, characterized in that: Also includes: The popular video screening module is used to screen the popular videos in the active track content to obtain popular video data.
8. The method for acquiring customers from public domain to private domain based on a large model according to claim 7, characterized in that: Also includes: The hot post screening module is used to extract the hot comments of the hot video data to obtain the hot comment data.
9. An electronic device, characterized in that: The electronic device includes a processor, the processor is coupled to a memory, at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor so that the electronic device can implement the large model-based automated public-domain to private-domain customer acquisition method as described in any one of claims 4 to 8.
10. A computer-readable storage medium, characterized in that: At least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by the processor so that the computer-readable storage medium implements the large-model-based automated public-domain-to-private-domain customer acquisition method as described in any one of claims 4 to 8.