Information processing method, device and equipment

Abstract

Embodiments of the invention disclose an information processing method, apparatus and device. The method comprises the steps of determining benefit point information for a to-be-released target object; the interest point information is analyzed according to a preset putting plan of a target object, an analysis result corresponding to the putting plan is obtained, and the putting plan includes putting putting information for the target object to a plurality of different putting booths; based on an analysis result corresponding to the putting plan and the benefit point information, constructing prompt information, inputting the prompt information into an object putting large model, and generating putting information of a target object corresponding to each putting booth in a plurality of different putting booths; and putting the putting information of the target object corresponding to each putting booth to the corresponding putting booth for display.

Description

Technical Field

[0001] This document relates to the field of computer technology, and in particular to an information processing method, device and equipment. Background Art

[0002] During the information delivery process, information about the same target audience is often delivered to multiple different delivery booths. At the same time, multiple different delivery booths will make some fine-tuning to the above information content. Normally, in the case of user privacy information, customized information delivery will be made based on each delivery booth, which requires separate development and processing at each link node such as information production, information delivery, and information analysis. At the same time, each business update will be processed using scattered configurations at different delivery booths to make corresponding fine-tuning based on the original business. Each fine-tuning requires development and adjustment at each delivery booth. To this end, a better way of information delivery is needed. Summary of the Invention

[0003] The purpose of the embodiments of this specification is to provide a better way to deliver information.

[0004] In order to implement the above technical solution, the embodiments of this specification are implemented as follows: An information processing method provided in an embodiment of the present specification includes: determining interest point information for a target object to be delivered; parsing the interest point information according to a pre-set delivery plan for the target object to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to multiple different delivery booths; constructing prompt information based on the parsing result corresponding to the delivery plan and the interest point information, and inputting the prompt information into an object delivery model to generate delivery information of the target object corresponding to each of multiple different delivery booths; and delivering the delivery information of the target object corresponding to each delivery booth to the corresponding delivery booth for display.

[0005] An embodiment of the present specification provides an information processing device, which includes: an information determination module, which determines interest point information for a target object to be delivered; a parsing module, which parses the interest point information according to a pre-set delivery plan for the target object to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to multiple different delivery booths; a delivery information generation module, which constructs prompt information based on the parsing result corresponding to the delivery plan and the interest point information, and inputs the prompt information into an object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths; and a delivery display module, which delivers the delivery information for the target object corresponding to each delivery booth to the corresponding delivery booth for display.

[0006] An embodiment of the present specification provides an information processing device, which includes: a processor; and a memory arranged to store computer-executable instructions, wherein the executable instructions, when executed, cause the processor to: determine interest point information for a target object to be delivered; parse the interest point information according to a pre-set delivery plan for the target object to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to multiple different delivery booths; construct prompt information based on the parsing result corresponding to the delivery plan and the interest point information, and input the prompt information into an object delivery model to generate delivery information of the target object corresponding to each of the multiple different delivery booths; and deliver the delivery information of the target object corresponding to each delivery booth to the corresponding delivery booth for display.

[0007] An embodiment of this specification also provides a storage medium, which is used to store computer-executable instructions, and when the executable instructions are executed by a processor, implements the following process: determining interest point information for the target object to be delivered; parsing the interest point information according to a pre-set delivery plan for the target object to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to multiple different delivery booths; constructing prompt information based on the parsing result corresponding to the delivery plan and the interest point information, and inputting the prompt information into the object delivery model to generate delivery information of the target object corresponding to each delivery booth in multiple different delivery booths; delivering the delivery information of the target object corresponding to each delivery booth to the corresponding delivery booth for display.

[0008] The embodiments of this specification also provide a computer program product, including a computer program, which implements the following process when executed by a processor: determining interest point information for a target object to be delivered; parsing the interest point information according to a pre-set delivery plan for the target object to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to multiple different delivery booths; constructing prompt information based on the parsing result corresponding to the delivery plan and the interest point information, and inputting the prompt information into an object delivery model to generate delivery information of the target object corresponding to each of multiple different delivery booths; and delivering the delivery information of the target object corresponding to each delivery booth to the corresponding delivery booth for display. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some of the embodiments described in this specification. Those skilled in the art can also derive other drawings based on these drawings without inventive work. Figure 1 This is a schematic diagram of the structure of an information processing system in this manual; Figure 2 This is a flowchart of an information processing method in this manual; Figure 3 A schematic diagram of an information processing process including prompt information construction in this specification; Figure 4 This is a schematic diagram of an information processing process in this manual; Figure 5 This is a schematic diagram of the information processing process for sound financial management in this manual; Figure 6 This is a schematic diagram of the hierarchical composition of an information processing system in this specification; Figure 7 This is a schematic diagram of an information processing device in this specification; Figure 8 This is a schematic diagram of an information processing device in this manual. DETAILED DESCRIPTION

[0010] The embodiments of this specification provide an information processing method, apparatus, and device.

[0011] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments derived by those skilled in the art based on the embodiments in this specification without creative effort shall fall within the scope of protection of this specification.

[0012] The embodiments of this specification provide an information delivery mechanism. Under normal circumstances, customized information delivery will be made based on each delivery booth, and manual adjustment is required. However, the same delivery information cannot be collected as data and is relatively scattered. Moreover, according to the requirements of different delivery booths, it is necessary to manually think about how to adjust the external copywriting and information. In addition, the generation of delivery information needs to be completed manually, which makes it inefficient. To this end, through the abstraction of interest point information and delivery booths, information delivery is carried out in combination with the differentiated information of the delivery booths and the delivery scenarios. When information is delivered, the interest point information is used as the most basic information. At different delivery booths, the booth customization processing will perform a rough processing on the interest point information. Finally, the processed information will be processed again in the scene dimension in the scene, thereby improving the generation efficiency of delivery information. For specific processing, please refer to the specific content in the following embodiments.

[0013] The information processing method provided in one or more embodiments of this specification can be applied to the implementation environment of information processing. Figure 1 , the implementation environment includes at least: Client 100 and server 200, where: The client 100 can run on a terminal device, which can be a mobile phone, a personal computer, a tablet computer, an e-book reader, a wearable device, a device that interacts with information based on AR (Augmented Reality) or VR (Virtual Reality), a laptop computer, etc. The terminal device can install the client 100, which can be an application, a browser, or a subroutine installed in an application, etc.

[0014] The server 200 can run on a server, which can be one or more servers, a server cluster consisting of several servers, or a cloud server of a cloud computing platform. The server can install the server 200, which can be an application or a subroutine installed in an application.

[0015] The object delivery model can be integrated into the server 200, or the server 200 can call the object delivery model to perform corresponding operations. In addition, the object delivery model can also be integrated into the client 100, or the client 100 can call the object delivery model to perform corresponding operations. In addition, a database can be included. The database can be set up in the server running the server 200 or outside the server running the server 200. The database can store relevant information such as the interest point information of different objects.

[0016] In this implementation environment, the server 200 can determine the interest point information for the target object to be delivered, and then, can parse the interest point information according to the pre-set delivery plan for the target object to obtain the parsing result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Afterwards, based on the parsing result and interest point information corresponding to the delivery plan, prompt information can be constructed, and the prompt information can be input into the object delivery model to generate the delivery information of the target object corresponding to each delivery booth in multiple different delivery booths. Finally, the delivery information of the target object corresponding to each delivery booth can be delivered to the corresponding delivery booth for display.

[0017] like Figure 2 As shown, an embodiment of this specification provides an information processing method, and the execution subject of the method can be a terminal device or a server, etc., wherein the terminal device can be a mobile terminal device such as a mobile phone, a tablet computer, or a computer device such as a laptop or a desktop computer, or an IoT device (specifically such as a smart watch, a car-mounted device, etc.), etc., wherein the server can be an independent server, or a server cluster composed of multiple servers, etc. The server can be a background server for a financial business or an online shopping business, etc., or a background server for an application, etc. In this embodiment, the execution subject is a server as an example for detailed description. For the case where the execution subject is a terminal device, please refer to the following server case processing, which will not be repeated here. The method can specifically include the following steps: In step S202, the interest point information for the target object to be delivered is determined.

[0018] Target objects can include multiple categories. For example, a target object can be a specific commodity or product, such as a certain brand of mobile phone, a fund product, an insurance product, or an annual membership card. A target object can also be a specific type of information, such as a recommendation for a university. The specific settings can be determined based on actual circumstances. Point of interest information can be information related to the target object's delivery process, such as one or more of the following: target object related information (such as the target object's name, code, or other identification information), information about the delivery booth, and user related historical information. The specific settings can be determined based on actual circumstances.

[0019] During implementation, the interest point information for the target object to be delivered can be determined in a variety of different ways. For example, the interest point information for the target object to be delivered can be provided by a user or a technician. The interest point information provided by the user or the technician can be set based on expert experience, or it can be set according to the situation of the target object (such as the business situation of the target object or the role and use of the target object, etc.). It can be set specifically according to actual conditions. For another example, historical data related to the target object can be obtained, and then, based on the analysis of the historical data, the interest point information for the target object to be delivered can be determined. For another example, a corresponding network model (such as a neural network model or a large language model, etc.) can be pre-trained. The network model can generate interest point information for a specified object. Then, data related to the target object can be obtained, and the obtained data can be input into the above-mentioned network model to obtain the interest point information for the target object to be delivered, etc. It can be set specifically according to actual conditions.

[0020] In step S204, the interest point information is parsed according to a preset delivery plan for the target object to obtain a parsing result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to a plurality of different delivery booths.

[0021] The placement plan can be a plan that includes data related to the placement of the target object, including the placement booths where the placement information for the target object is to be placed. The placement plan can include placing the placement information for the target object at multiple different placement booths. The placement information for the target object can be information related to the target object that needs to be placed. For example, if the target object is Fund A, the placement information for the target object can be information such as Fund A's average return over the past year is 1.4%, the return is calculated daily, the historical daily return is positive, it can be paid for, and the return can be enjoyed without worry, etc. The specific settings can be based on actual conditions.

[0022] During implementation, a target placement plan can be set based on actual conditions. This placement plan can be set based on placement needs. Once set, the placement plan can be used to parse the aforementioned interest point information. This analysis can reveal which placement booths need to be placed, the location of each placement booth, the characteristics of each placement booth, the differences between different placement booths, the current status of the target object, and the status of the business to which the target object belongs. The specific settings can be based on actual conditions. Through the above-mentioned parsing process, the parsing results corresponding to the placement plan can be obtained.

[0023] In step S206, based on the analysis results and interest point information corresponding to the above delivery plan, prompt information is constructed and input into the object delivery model to generate delivery information of the target object corresponding to each of the multiple different delivery booths.

[0024] The object delivery model can be a large model that generates corresponding delivery information for different delivery booths. It can be composed of billions of parameters, based on deep learning algorithms and pre-trained using large-scale corpora. For example, the object delivery model can be a model built using LLM, a large model based on BERT, or a large model based on the Transformer architecture. Specifically, the object delivery model can include GPT-3, ERNIE Bot, etc., and the specific settings can be determined based on actual circumstances. Prompt information can be a prompt applied to the object delivery model. Prompt information is text input into the object delivery model to guide the object delivery model in generating output results that meet the requirements. Prompt information can be a question, an instruction, or a piece of context to help the object delivery model better understand and respond to various queries. Prompt information can include clear instruction prompts, context-supplementing prompts, and example-guided prompts. Prompt information helps the object delivery model generate more relevant and accurate output results by providing detailed background information and examples.

[0025] During implementation, a suitable algorithm or network can be selected based on actual conditions to pre-set the model architecture of the object placement model. Then, training data and corresponding label information for training the object placement model can be obtained. An object placement model can be pre-trained or directly obtained from a designated database. This model can serve as a pre-trained object placement model, which can generate corresponding placement information for different placement booths. Corresponding prompt information (i.e., the prompt of the object placement model) can be generated based on the training data. The training data can be analyzed and processed by the object placement model, and a result can ultimately be output. The loss information between the output result and the label information can be calculated. The object placement model can be adjusted based on this loss information. The above process is iteratively executed until the loss function corresponding to the corresponding loss information converges, ultimately obtaining the object placement model. Through the above model training, a large model capable of generating corresponding placement information for different placement booths can be obtained.

[0026] After obtaining the analysis results corresponding to the above-mentioned delivery plan in the above-mentioned manner, prompt information can be constructed based on the analysis results and interest point information corresponding to the above-mentioned delivery plan, and the prompt information can be input into the object delivery model. Alternatively, the prompt information, the analysis results corresponding to the delivery plan, the interest point information and other related information can be input into the object delivery model. The input information is analyzed and processed by the object delivery model, and based on the characteristics and differences between different delivery booths obtained from the analysis, the delivery information of the target object corresponding to each of the multiple different delivery booths is generated.

[0027] In step S208, the delivery information of the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display.

[0028] In implementation, through the above method, the delivery information of the target object corresponding to each of multiple different delivery booths can be obtained. For example, the delivery booths include booth A, booth B, and booth C. Information 1 can be generated for booth A, information 2 can be generated for booth B, and information 3 can be generated for booth C. Then, information 1 can be delivered to booth A, information 2 can be delivered to booth B, and information 3 can be delivered to booth C. In this way, when the user opens the specified page, the corresponding delivery information can be displayed on the delivery booth in the specified page.

[0029] Embodiments of this specification provide an information processing method. By determining interest point information for a target object to be delivered, the interest point information can be parsed according to a pre-set delivery plan for the target object to obtain a parsed result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Subsequently, prompt information can be constructed based on the parsed result and interest point information corresponding to the delivery plan. The prompt information is input into a large object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths. Finally, the delivery information for the target object corresponding to each delivery booth can be delivered to the corresponding delivery booth for display. In this way, information delivery is performed by abstracting the interest point information and the delivery booth, while combining the differentiated information of the delivery booth and the delivery scenario. During information delivery, the interest point information serves as the most basic information. At different delivery booths, booth customization processing will perform a rough processing on the interest point information. Finally, the processed information will be further processed in the scenario dimension, thereby improving the efficiency of delivery information generation.

[0030] In actual applications, the specific processing methods of the above-mentioned step S202 can be various. An optional processing method is provided below, which may specifically include the following: obtaining interest point information for the target object provided by the user; and / or obtaining historical interest point information for the target object and / or a first object related to the target object, and determining the interest point information based on the obtained historical interest point information.

[0031] During implementation, the user himself can provide the interest point information for the target object. In addition, the interest point information currently needed can be constructed through historical information. For example, the historical interest point information for the target object can be obtained, and the interest point information for this delivery can be constructed based on the historical interest point information for the target object. Specifically, if the historical interest point information includes interest point 1, interest point 2, interest point 3 and interest point 4, and interest point 1 and interest point 3 have good delivery effects, while interest point 2 and interest point 4 have no obvious or poor delivery effects, then interest point 1 and interest point 3 can be determined as the interest point information for this delivery, etc. The specific details can also be set according to actual conditions. In addition, historical interest point information of a first object related to the target object can also be obtained, and interest point information for this delivery can be constructed based on the historical interest point information of the first object, wherein the first object can be any one or more objects related to the target object. For example, if the target object is a mobile phone of brand A, the first object can be another model or multiple other mobile phones of brand A, or a mobile phone of the same or similar model of other brands, or other electronic products of brand A or other brands (such as tablets, laptops, speakers, watches, bracelets, etc.). In actual applications, the historical interest point information of the first object can be directly used as the interest point information for this delivery, or a certain number of historical interest point information can be selected from the historical interest point information of the first object as the interest point information for this delivery. As mentioned above, historical interest point information with better delivery effect can also be selected as the interest point information for this delivery. The specific setting can also be based on actual conditions.

[0032] In addition, the interest point information of this delivery can be determined through a combination of two or three of the above three methods. For example, the user can provide a part of the interest point information for the target object, and then determine a part of the interest point information through the historical interest point information of the target object. The user can also provide a part of the interest point information for the target object, and then determine a part of the interest point information through the historical interest point information of the first object, etc. The specific settings can be made according to actual conditions.

[0033] It should be noted that, for information such as point of interest information provided by users or technical personnel, the information content can be recognized through character detection and recognition algorithms (such as OCR (Optical Character Recognition) algorithms, etc.).

[0034] In actual application, the specific processing methods for constructing prompt information based on the analysis results and interest point information corresponding to the above delivery plan in step S206 can be varied. The following provides an optional processing method. For details, please refer to the processing of steps S2062 to S2066 below. Based on this, in the above Figure 2Based on this, the method specifically includes the following steps: Figure 3 shown.

[0035] In step S2062, description information of the point of interest information is generated based on the point of interest information.

[0036] In implementation, a generation rule of the description information may be constructed in advance according to a specified information language, and then, the description information of the interest point information may be generated based on the interest point information through the information language in the generation rule of the description information.

[0037] In step S2064, the difference information between the multiple different placement booths, the description information corresponding to the multiple different placement booths, and the description information of the difference information are obtained.

[0038] During implementation, multiple different placement booths can be analyzed in advance to determine the differences between the multiple different placement booths, or the user or technician can directly provide the difference information between the multiple different placement booths. Afterwards, the information language in the descriptive information generation rules can be used to generate descriptive information corresponding to the multiple different placement booths based on the multiple different placement booths. The information language in the descriptive information generation rules can also be used to generate descriptive information of the difference information based on the above-mentioned difference information.

[0039] In step S2066, prompt information is constructed based on the description information of the interest point information, the difference information between the multiple different placement booths, the description information corresponding to the multiple different placement booths, and the description information of the difference information.

[0040] In practical applications, such as Figure 4 As shown, an effect analysis mechanism can also be set up to determine the display effect that can be achieved by the above-mentioned interest point information through the effect analysis mechanism, and the obtained analysis results are fed back to the above-mentioned interest point determination process to adjust the current interest point information. For details, please refer to the processing of steps A2 and A4 below.

[0041] In step A2, display effect information of the target object's delivery information corresponding to each delivery booth is obtained at the corresponding delivery booth.

[0042] Among them, the display effect information may include a variety of information. For example, the display effect information may include the number of users viewing or accessing the delivery information, the length of time the user stays on the page of the delivery information, etc., which can be set according to actual conditions.

[0043] In step A4, the determined interest point information is adjusted based on the acquired display effect information, so as to generate placement information on each placement booth for display based on the adjusted interest point information.

[0044] In implementation, for example, if the display effect information corresponding to a certain interest point information indicates that the number of users accessing the delivery information is the least, then the interest point information can be eliminated from the above-mentioned determined interest point information, or the interest point information corresponding to the display effect information in which the number of users accessing the delivery information is less than a preset threshold can be eliminated from the above-mentioned determined interest point information. The specific setting can be based on actual conditions.

[0045] In practical applications, such as Figure 4 As shown, an operation and maintenance management mechanism for the interest point information may also be set up to manage the above interest point information through the operation and maintenance management mechanism for the interest point information. For details, please refer to the processing of the following steps B2 and B4.

[0046] In step B2, a logoff request of the first interest point information in the determined interest point information is received, where the logoff request includes identification information of the first interest point information.

[0047] In step B4, based on the identification information, the first interest point information is removed from the determined interest point information.

[0048] In practical applications, such as Figure 4 As shown, an interest point experiment mechanism may also be set up to perform designated experimental processing on the interest point information through the interest point experiment mechanism. For details, please refer to the processing of the following steps C2 and C4.

[0049] In step C2, an experiment is conducted on the interest point information of the target object based on preset experimental rules to obtain corresponding experimental results.

[0050] The experimental rules may be rules for conducting specified experiments on the interest point information of the target object, wherein the specified experiments may include experiments on the importance of interest point information, experiments on the increment of interest point information, etc., which may be specifically set according to actual conditions.

[0051] In step C4, the interest point information is adjusted based on the obtained experimental results, so as to generate placement information for display on each placement booth based on the adjusted interest point information.

[0052] In practical applications, interest point information may include target object information, user behavior information, and scene atmosphere information. The object delivery model is a large model constructed through a large language model.

[0053] In practical applications, the target object may include a financial product in a financial management business or an advertisement object.

[0054] Embodiments of this specification provide an information processing method. By determining interest point information for a target object to be delivered, the interest point information can be parsed according to a pre-set delivery plan for the target object to obtain an analysis result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Subsequently, prompt information can be constructed based on the analysis result and interest point information corresponding to the delivery plan. The prompt information is input into a large object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths. Finally, the delivery information for the target object corresponding to each delivery booth can be delivered to the corresponding delivery booth for display. In this way, information delivery is performed by abstracting the interest point information and the delivery booth, while combining the differentiated information of the delivery booth and the delivery scenario. During information delivery, the interest point information serves as the most basic information. At different delivery booths, booth customization processing performs a rough processing on the interest point information. Finally, the processed information is further processed in the scenario dimension. In addition, due to the provision of descriptive information, the delivery information is generated by combining the interest point information, the delivery booth, and the scene atmosphere information, thereby improving the efficiency of delivery information generation.

[0055] The following is a detailed description of an information processing method provided in an embodiment of this specification in combination with a specific application scenario, wherein the target object may be a stable fund product, the interest point information may include information on the stable fund product, user behavior information and scene atmosphere information, and the object delivery large model is a large model constructed through a large language model.

[0056] The embodiments of this specification provide an information processing method, the execution subject of the method can be a terminal device or a server, etc., wherein the terminal device can be a mobile terminal device such as a mobile phone, a tablet computer, or a computer device such as a laptop or a desktop computer, or an IoT device (specifically such as a smart watch, a car-mounted device, etc.), etc., wherein the server can be an independent server, or a server cluster composed of multiple servers, etc. The server can be a background server for a financial business or an online shopping business, etc., or a background server for an application, etc. In this embodiment, the execution subject is described in detail as an example of a server. For the case where the execution subject is a terminal device, please refer to the following server case processing, which will not be repeated here. The method can specifically include the following steps: In step D02, the interest point information for the stable fund product provided by the user is obtained; and / or, the historical interest point information for the stable fund product and / or the first wealth management product related to the stable fund product is obtained, and based on the obtained historical interest point information, the interest point information including the information of the stable fund product, the user behavior information and the scene atmosphere information is determined.

[0057] In implementation, Figure 5 As shown, the stable fund product is xx positive return, and a stable knowledge base can be pre-set, which may include interest point configuration, template configuration and scenario configuration. The interest point configuration includes list, xx zone, xx shelf, xx positive return, and xx positive return may include xx positive return supply pool, xx positive return months, xx positive return chart and xx positive return copy. The template configuration includes A placement booth strategy, total assets, stable fund booth strategy, etc. The scenario configuration may include stable product external investment, A placement booth external investment, total asset investment, etc. Based on this, the interest point information for stable fund products provided by users can be stored in the stable knowledge base. Then, the interest point information for stable fund products can be obtained from the stable knowledge base, and the historical interest point information for stable fund products and / or the first wealth management products related to stable fund products can also be obtained from the stable knowledge base. As Figure 5 As shown, the stable business party, the A booth business party, and the total asset business party can deposit the corresponding interest point information into the stable knowledge base. Subsequently, the interest point information or related historical interest point information for stable fund products can be obtained from the stable knowledge base.

[0058] In step D04, the interest point information is parsed according to a pre-set placement plan for a stable fund product to obtain a parsing result corresponding to the placement plan. The placement plan includes placing the placement information for the stable fund product at a plurality of different placement booths.

[0059] Among them, Figure 5 As shown, multiple different placement booths may include a stable fund placement booth, an A placement booth, and a total asset placement booth, etc.

[0060] In step D06, description information of the point of interest information is generated based on the point of interest information.

[0061] In step D08 , the difference information between the multiple different placement booths, the description information corresponding to the multiple different placement booths, and the description information of the difference information are obtained.

[0062] In step D10 , prompt information is constructed based on the description information of the interest point information, the difference information between the multiple different placement booths, the description information corresponding to the multiple different placement booths, and the description information of the difference information.

[0063] In implementation, Figure 5As shown, for the stable business side, the corresponding prompt information can be constructed based on the stable fund booth strategy through the description information of the interest point information, the difference information between different placement booths, the description information corresponding to multiple different placement booths, and the description information of the difference information. For the A placement booth business side, the corresponding prompt information can be constructed based on the A placement booth strategy through the description information of the interest point information, the difference information between different placement booths, the description information corresponding to multiple different placement booths, and the description information of the difference information. For the total asset business side, the corresponding prompt information can be constructed based on the total asset booth strategy through the description information of the interest point information, the difference information between different placement booths, the description information corresponding to multiple different placement booths, and the description information of the difference information.

[0064] In step D12, the prompt information is input into the object placement model to generate placement information of the stable fund product corresponding to each of the multiple different placement booths.

[0065] In step D14, the placement information of the stable fund product corresponding to each placement booth is placed at the corresponding placement booth for display.

[0066] In implementation, Figure 5 As shown, the corresponding placement information generated above can be placed in the stable fund booth, A placement booth and total asset placement booth respectively.

[0067] In step D16, the display effect information of the placement information of the stable fund product corresponding to each placement booth is obtained at the corresponding placement booth.

[0068] In step D18, the determined interest point information is adjusted based on the acquired display effect information, so as to generate placement information for display on each placement booth based on the adjusted interest point information.

[0069] In step D20, a logoff request of the first interest point information in the determined interest point information is received, where the logoff request includes identification information of the first interest point information.

[0070] In step D22, based on the identification information, the first point of interest information is removed from the determined point of interest information.

[0071] In step D24, an experiment is conducted on the interest point information of the stable fund product based on the preset experimental rules to obtain corresponding experimental results.

[0072] In step D26 , the interest point information is adjusted based on the obtained experimental results, so as to generate placement information for display on each placement booth based on the adjusted interest point information.

[0073] Embodiments of this specification provide an information processing method. By determining interest point information for a target object to be delivered, the interest point information can be parsed according to a pre-set delivery plan for the target object to obtain an analysis result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Subsequently, prompt information can be constructed based on the analysis result and interest point information corresponding to the delivery plan. The prompt information is input into a large object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths. Finally, the delivery information for the target object corresponding to each delivery booth can be delivered to the corresponding delivery booth for display. In this way, information delivery is performed by abstracting the interest point information and the delivery booth, while combining the differentiated information of the delivery booth and the delivery scenario. During information delivery, the interest point information serves as the most basic information. At different delivery booths, booth customization processing performs a rough processing on the interest point information. Finally, the processed information is further processed in the scenario dimension. In addition, due to the provision of descriptive information, the delivery information is generated by combining the interest point information, the delivery booth, and the scene atmosphere information, thereby improving the efficiency of delivery information generation.

[0074] The above is an information processing method provided by the embodiment of this specification. The embodiment of this specification also provides an information processing system, such as Figure 6 shown.

[0075] The information processing system includes an infrastructure layer, a basic domain layer, a scenario domain layer, and an application layer, among which: The infrastructure layer is at the bottom, the basic domain layer is above the infrastructure layer, the scenario domain layer is above the basic domain layer, and the application layer is at the top.

[0076] The infrastructure layer mainly includes the database DAO layer, character detection and recognition algorithms such as OCR algorithms, and AIGC, etc. Through the above-mentioned database DAO layer, character detection and recognition algorithms such as OCR algorithms, and AIGC, etc., the most basic shared capabilities can be provided for the information processing system.

[0077] The basic domain layer consists of the scenario domain and the interest point domain. The interest point domain primarily maintains interest point information and related information, and also includes advanced features such as interest point information mining. The scenario domain primarily includes the differentiated configurations between different advertising booths, and customized information configuration and logic for different advertising scenarios and booths.

[0078] The scenario domain layer is mainly based on the basic domain layer, and superimposes the high-level characteristics of various delivery scenarios. For example, in the scenario of interest point mining, character detection and recognition algorithms such as OCR algorithms are used to identify relevant information provided by users or technicians. At the same time, AIGC capabilities are combined to summarize the relevant information provided by users or technicians and produce delivery information according to the information language requirements in the descriptive information generation rules. The scenario domain layer can customize the corresponding scenario layer. Therefore, the mining model can be customized in the scenario domain layer. At the same time, the description information of the scenario and interest point information is combined with the large model customized for the scenario to automatically generate new interest point information and subsequent overall delivery. At the same time, in order to improve the accuracy of the description information of the interest point information, the description information of each interest point information is dynamically adjusted through the feedback mechanism of data analysis.

[0079] The application layer mainly encapsulates the external functions of each domain layer, and serves as an external interface and functional interface display.

[0080] The information processing system can achieve the following processing through its functional layers including infrastructure layer, basic domain layer, scenario domain layer and application layer: determine the interest point information for the target object to be delivered, and then parse the interest point information according to the pre-set delivery plan for the target object to obtain the analysis results corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Afterwards, prompt information can be constructed based on the analysis results and interest point information corresponding to the delivery plan, and the prompt information can be input into the object delivery model to generate the delivery information of the target object corresponding to each delivery booth in multiple different delivery booths. Finally, the delivery information of the target object corresponding to each delivery booth can be delivered to the corresponding delivery booth for display.

[0081] Embodiments of this specification provide an information processing system that determines interest point information for a target object to be delivered. The interest point information is then parsed according to a pre-set delivery plan for the target object, resulting in an analysis result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Subsequently, prompt information is constructed based on the parsed result and interest point information corresponding to the delivery plan. The prompt information is input into a large object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths. Finally, the delivery information for the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display. In this way, information delivery is performed by abstracting the interest point information and the delivery booth, while combining differentiated information about the delivery booth and the delivery scenario. During information delivery, the interest point information serves as the most basic information. At different delivery booths, booth customization performs a rough processing on the interest point information, and finally, the processed information is further processed in the scenario dimension. Furthermore, due to the provision of descriptive information, the delivery information is generated by combining the interest point information, the delivery booth, and the scene atmosphere information, thereby improving the efficiency of delivery information generation.

[0082] The above is an information processing method and system provided by the embodiments of this specification. Based on the same idea, the embodiments of this specification also provide an information processing device, such as Figure 7 shown.

[0083] The information processing device includes: an information determination module 701, an analysis module 702, a delivery information generation module 703 and a delivery display module 704, wherein: Information determination module 701, determining the interest point information for the target object to be delivered; The parsing module 702 parses the interest point information according to a pre-set target object delivery plan to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to a plurality of different delivery booths; The delivery information generation module 703 constructs prompt information based on the analysis results corresponding to the delivery plan and the interest point information, and inputs the prompt information into the object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths; The delivery and display module 704 delivers the delivery information of the target object corresponding to each delivery booth to the corresponding delivery booth for display.

[0084] In the embodiment of this specification, the information determination module 701 includes: The first information determining unit obtains the interest point information of the target object provided by the user; and / or The second information determining unit acquires historical interest point information for the target object and / or a first object related to the target object, and determines the interest point information based on the acquired historical interest point information.

[0085] In the embodiment of this specification, the delivery information generation module 703 includes: a first description information acquisition unit, configured to generate description information of the interest point information based on the interest point information; A second description information acquisition unit is configured to acquire difference information between a plurality of different placement booths, description information corresponding to the plurality of different placement booths, and description information of the difference information; The prompt information constructing unit constructs prompt information based on the description information of the interest point information, the difference information between the multiple different placement booths, the description information corresponding to the multiple different placement booths, and the description information of the difference information.

[0086] In the embodiment of this specification, the device further includes: The effect acquisition module obtains the display effect information of the target object corresponding to each placement booth at the corresponding placement booth; The first adjustment module adjusts the determined interest point information based on the acquired display effect information, so as to generate placement information on each placement booth for display based on the adjusted interest point information.

[0087] In the embodiment of this specification, the device further includes: A request receiving module, receiving a logoff request for a first interest point information in the determined interest point information, wherein the logoff request includes identification information of the first interest point information; A removal module removes the first interest point information from the determined interest point information based on the identification information.

[0088] In the embodiment of this specification, the device further includes: The experimental module conducts experiments on the interest point information of the target object based on the preset experimental rules and obtains the corresponding experimental results; The second adjustment module adjusts the interest point information based on the obtained experimental results, so as to generate placement information on each placement booth for display based on the adjusted interest point information.

[0089] In the embodiment of this specification, the interest point information includes target object information, user behavior information and scene atmosphere information, and the object delivery large model is a large model constructed by a large language model.

[0090] In the embodiment of this specification, the target object includes a financial product in a financial management business or an advertisement object.

[0091] Embodiments of this specification provide an information processing device that determines interest point information for a target object to be delivered. The interest point information is then parsed according to a pre-set delivery plan for the target object to obtain an analysis result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Subsequently, prompt information is constructed based on the analysis result and interest point information corresponding to the delivery plan. The prompt information is input into a large object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths. Finally, the delivery information for the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display. In this way, information delivery is performed by abstracting the interest point information and the delivery booth, while combining differentiated information about the delivery booth and the delivery scenario. During information delivery, the interest point information serves as the most basic information. At different delivery booths, booth customization processing performs a rough processing on the interest point information, and finally, the processed information is further processed in the scenario dimension. Furthermore, due to the provision of descriptive information, the delivery information is generated by combining the interest point information, the delivery booth, and scene atmosphere information, thereby improving the efficiency of delivery information generation.

[0092] The above is an information processing device provided by the embodiment of this specification. Based on the same idea, the embodiment of this specification also provides an information processing device, such as Figure 8 shown.

[0093] The information processing device may provide a terminal device or a server, etc. for the above embodiments.

[0094] Information processing devices can vary significantly depending on their configuration or performance. They may include one or more processors 801 and memory 802. Memory 802 may store one or more applications or data. Memory 802 may be either ephemeral or persistent. Applications stored in memory 802 may include one or more modules (not shown), each of which may include a series of computer-executable instructions for the information processing device. Furthermore, processor 801 may be configured to communicate with memory 802 to execute the series of computer-executable instructions in memory 802 on the information processing device. Information processing devices may also include one or more power supplies 803, one or more wired or wireless network interfaces 804, one or more input / output interfaces 805, and one or more keyboards 806.

[0095] Specifically, in this embodiment, the information processing device includes a memory and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may include one or more modules, and each module may include a series of computer-executable instructions for the information processing device, and the one or more programs are configured to be executed by one or more processors, including computer-executable instructions for performing the following: Determine the interest point information for the target objects to be delivered; Parsing the interest point information according to a pre-set target object delivery plan to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to a plurality of different delivery booths; Based on the analysis results corresponding to the delivery plan and the interest point information, construct prompt information, and input the prompt information into the object delivery model to generate delivery information of the target object corresponding to each of the multiple different delivery booths; The delivery information of the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display.

[0096] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences between the other embodiments. In particular, the information processing device embodiment is generally similar to the method embodiment, so the description is relatively simple. For relevant portions, refer to the description of the method embodiment.

[0097] Embodiments of this specification provide an information processing device that determines interest point information for a target object to be delivered. The interest point information is then parsed according to a pre-set delivery plan for the target object, resulting in an analysis result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Subsequently, prompt information is constructed based on the parsed result and interest point information corresponding to the delivery plan. The prompt information is input into a large object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths. Finally, the delivery information for the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display. In this way, information delivery is performed by abstracting the interest point information and the delivery booth, while combining differentiated information about the delivery booth and the delivery scenario. During information delivery, the interest point information serves as the most basic information. At different delivery booths, booth customization processing performs a rough processing on the interest point information, and finally, the processed information is further processed in the scenario dimension. Furthermore, due to the provision of descriptive information, the delivery information is generated by combining the interest point information, the delivery booth, and scene atmosphere information, thereby improving the efficiency of delivery information generation.

[0098] Furthermore, based on the above Figures 2 to 5 One or more embodiments of this specification further provide a storage medium for storing computer-executable instruction information. In a specific embodiment, the storage medium may be a USB flash drive, an optical disk, a hard disk, etc. When the computer-executable instruction information stored in the storage medium is executed by a processor, the following process can be implemented: Determine the interest point information for the target objects to be delivered; Parsing the interest point information according to a pre-set target object delivery plan to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to a plurality of different delivery booths; Based on the analysis results corresponding to the delivery plan and the interest point information, construct prompt information, and input the prompt information into the object delivery model to generate delivery information of the target object corresponding to each of the multiple different delivery booths; The delivery information of the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display.

[0099] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences from the other embodiments. In particular, the aforementioned storage medium embodiment is generally similar to the method embodiment, so its description is relatively simple. For relevant portions, refer to the description of the method embodiment.

[0100] Embodiments of this specification provide a storage medium that determines interest point information for a target object to be delivered. The interest point information is then parsed according to a pre-set delivery plan for the target object to obtain a parsed result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Subsequently, prompt information is constructed based on the parsed result and interest point information corresponding to the delivery plan. The prompt information is input into a large object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths. Finally, the delivery information for the target object corresponding to each delivery booth can be delivered to the corresponding delivery booth for display. In this way, information delivery is performed by abstracting the interest point information and the delivery booth, while combining differentiated information about the delivery booth and the delivery scenario. During information delivery, the interest point information serves as the most basic information. At different delivery booths, booth customization performs a rough processing on the interest point information, and finally, the processed information is further processed in the scenario dimension. Furthermore, due to the provision of descriptive information, the delivery information is generated by combining the interest point information, the delivery booth, and scene atmosphere information, thereby improving the efficiency of delivery information generation.

[0101] Furthermore, based on the above Figures 2 to 5 One or more embodiments of this specification further provide a computer program product, including a computer program. When the computer program in the computer program product is executed by a processor, it can implement the following process: Determine the interest point information for the target objects to be delivered; Parsing the interest point information according to a pre-set target object delivery plan to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to a plurality of different delivery booths; Based on the analysis results corresponding to the delivery plan and the interest point information, construct prompt information, and input the prompt information into the object delivery model to generate delivery information of the target object corresponding to each of the multiple different delivery booths; The delivery information of the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display.

[0102] The various embodiments in this specification are described in a progressive manner. Similar portions between the various embodiments can be referenced to each other. Each embodiment focuses on the differences between the other embodiments. In particular, the aforementioned computer program product embodiment is generally similar to the method embodiment, so its description is relatively simple. For relevant portions, reference can be made to the description of the method embodiment.

[0103] Embodiments of this specification provide a computer program product that determines interest point information for a target object to be delivered. The interest point information is then parsed according to a pre-set delivery plan for the target object, resulting in an analysis result corresponding to the delivery plan. The delivery plan includes delivering the delivery information for the target object to multiple different delivery booths. Subsequently, prompt information is constructed based on the parsed result and interest point information corresponding to the delivery plan. The prompt information is input into a large object delivery model to generate delivery information for the target object corresponding to each of the multiple different delivery booths. Finally, the delivery information for the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display. In this way, information delivery is performed by abstracting the interest point information and the delivery booth, while combining differentiated information about the delivery booth and the delivery scenario. During information delivery, the interest point information serves as the most basic information. At different delivery booths, booth customization performs a rough processing on the interest point information, and finally, the processed information is further processed in the scenario dimension. Furthermore, due to the provision of descriptive information, the delivery information is generated by combining the interest point information, the delivery booth, and scene atmosphere information, thereby improving the efficiency of delivery information generation.

[0104] The foregoing description of this specification describes specific embodiments. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in an order different from that described in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order shown or the sequential order to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0105] In the 1990s, technological improvements could be clearly distinguished as either hardware improvements (for example, improvements to circuit structures like diodes, transistors, and switches) or software improvements (improvements to process flows). However, with the advancement of technology, many process flow improvements can now be considered direct improvements to hardware circuit structures. Designers almost always create the corresponding hardware circuit structure by programming the improved process flow into the hardware circuit. Therefore, it cannot be said that a process flow improvement cannot be implemented using physical hardware modules. For example, a programmable logic device (PLD), such as a field programmable gate array (FPGA), is an integrated circuit whose logical function is determined by user programming. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to hire a chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly performed using software called a "logic compiler." This is similar to the software compilers used during program development. Before compilation, the original code must be written in a specific programming language, called a Hardware Description Language (HDL). There are many types of HDL, including ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art will also understand that simply by programming a method flow in one of these hardware description languages ​​and then programming it into an integrated circuit, a hardware circuit that implements the logic method flow can be easily obtained.

[0106] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the memory control logic. Those skilled in the art will also appreciate that, in addition to implementing the controller purely in computer-readable program code, the controller can also be implemented in the form of logic gates, switches, an application-specific integrated circuit, a programmable logic controller, an embedded microcontroller, etc. by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the means for implementing the various functions included therein can also be considered as structures within the hardware component. Alternatively, the means for implementing the various functions can be considered both a software module implementing the method and a structure within the hardware component.

[0107] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0108] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0109] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Thus, one or more embodiments of this specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, one or more embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0110] The embodiments of this specification are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable fraud case serial and parallel device to produce a machine, so that the instructions executed by the processor of the computer or other programmable fraud case serial and parallel device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0111] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable fraud case serial and parallel device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, the instruction device being implemented in the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0112] These computer program instructions may also be loaded onto a computer or other programmable device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0113] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0114] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0115] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0116] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0117] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Thus, one or more embodiments of this specification may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, one or more embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0118] One or more embodiments of this specification may 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. One or more embodiments of this specification may also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communications network. In distributed computing environments, program modules may be located in local and remote computer storage media, including storage devices.

[0119] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0120] The foregoing is merely an example of the present invention and is not intended to limit this document. Various modifications and variations are possible within the scope of this document. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this document are intended to be included within the scope of the claims of this document.

Claims

1. An information processing method, comprising: Determine the interest point information for the target objects to be delivered; Parsing the interest point information according to a pre-set target object delivery plan to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to a plurality of different delivery booths; Based on the analysis results corresponding to the delivery plan and the interest point information, construct prompt information, and input the prompt information into the object delivery model to generate delivery information of the target object corresponding to each of the multiple different delivery booths; The delivery information of the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display.

2. The method according to claim 1, wherein determining the interest point information for the target object to be delivered comprises: Obtaining user-provided information on interest points for the target object; and / or, Historical point-of-interest information for a target object and / or a first object related to the target object is obtained, and the point-of-interest information is determined based on the obtained historical point-of-interest information.

3. The method according to claim 1 or 2, wherein constructing prompt information based on the analysis result corresponding to the delivery plan and the interest point information comprises: Based on the interest point information, generating description information of the interest point information; Obtaining difference information between a plurality of different placement booths, description information corresponding to the plurality of different placement booths, and description information of the difference information; Prompt information is constructed based on the description information of the interest point information, the difference information between the multiple different placement booths, the description information corresponding to the multiple different placement booths, and the description information of the difference information.

4. The method according to claim 3, further comprising: Obtain the display effect information of the target object's delivery information corresponding to each delivery booth at the corresponding delivery booth; The determined interest point information is adjusted based on the acquired display effect information, so as to generate placement information on each placement booth for display based on the adjusted interest point information.

5. The method according to claim 4, further comprising: receiving an offline request for first interest point information among the determined interest point information, wherein the offline request includes identification information of the first interest point information; Based on the identification information, the first interest point information is removed from the determined interest point information.

6. The method according to claim 5, further comprising: Conduct experiments on the target object's interest point information based on preset experimental rules and obtain corresponding experimental results; The interest point information is adjusted based on the obtained experimental results, so as to generate placement information on each placement booth for display based on the adjusted interest point information.

7. According to the method of claim 6, the interest point information includes information of the target object, user behavior information and scene atmosphere information, and the object delivery large model is a large model constructed by a large language model.

8. The method according to claim 7, wherein the target object comprises a financial product in a financial management business or an advertisement object.

9. An information processing device, comprising: An information determination module determines the interest point information of the target object to be delivered; a parsing module, which parses the interest point information according to a pre-set target object delivery plan to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to a plurality of different delivery booths; a delivery information generation module, which constructs prompt information based on the analysis results corresponding to the delivery plan and the interest point information, and inputs the prompt information into the object delivery model to generate delivery information of the target object corresponding to each of the multiple different delivery booths; The delivery display module delivers the delivery information of the target object corresponding to each delivery booth to the corresponding delivery booth for display.

10. An information processing device, comprising: processor; as well as a memory arranged to store computer-executable instructions which, when executed, cause the processor to: Determine the interest point information for the target objects to be delivered; Parsing the interest point information according to a pre-set target object delivery plan to obtain a parsing result corresponding to the delivery plan, wherein the delivery plan includes delivering the delivery information for the target object to a plurality of different delivery booths; Based on the analysis results corresponding to the delivery plan and the interest point information, construct prompt information, and input the prompt information into the object delivery model to generate delivery information of the target object corresponding to each of the multiple different delivery booths; The delivery information of the target object corresponding to each delivery booth is delivered to the corresponding delivery booth for display.

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