User rights and interests calculation method for hotel reservation service

Abstract

The user right calculation method is applied to an artificial intelligence service program which is deployed on a service platform and corresponds to a service provider. The artificial intelligence service program is a service program constructed based on LLM; the service provider issues an online service on the service platform; the method comprises the following steps: acquiring demand data input by a user; performing semantic recognition on the demand data, and determining the consumption demand of the user for the online service based on a semantic recognition result; the consumption demand comprises a consumption demand used for triggering calculation of user rights and interests which can be obtained by the user after service consumption is carried out on the online service; and in response to the determined consumption demand of the user for the online service, on the basis of basic information which is acquired from a service provider and is used for calculating the rights and interests of the user, calculating the number of points which can be obtained after the user performs service consumption corresponding to the consumption demand for the online service.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of artificial intelligence technology, and in particular to a user rights calculation method, computing device, and computer program product. Background Technology

[0002] For business purposes, some merchants often publish online service products on online service platforms. In order to increase user stickiness, after users consume these online service products, they usually give users some user benefits (such as points).

[0003] However, in practice, the user benefits issued to users usually involve a series of rules defined by the merchants. Users may not be familiar with these rules. Therefore, when users need to make calculations related to user benefits, if they rely entirely on manual calculations, it is not only complicated to operate, but also difficult to calculate accurate results.

[0004] For example, taking the aforementioned user benefits as points issued to users as an example, these rules may specifically include rules for the allocation of points, rules for upgrading or downgrading user benefit levels based on the points earned by users, and so on. If users are not familiar with these rules, it is difficult for them to accurately calculate the number of points they can obtain, and whether they can upgrade or downgrade based on their existing points, which greatly affects the user experience.

[0005] Moreover, when issuing user benefits, it is often necessary to integrate data from multiple sources to accurately calculate the number of user benefits issued to users. Therefore, it is quite difficult for both merchants and service platforms to accurately calculate the number of user benefits issued to users. In practical applications, there may be problems such as being unable to calculate (e.g., missing data) or the calculated number of user benefits being inaccurate. Summary of the Invention

[0006] This specification proposes a method for calculating user benefits for hotel booking services, applied to a target AI service program deployed on a service platform corresponding to a hotel brand; wherein, the target AI service program is a service program built based on LLM; the hotel brand publishes hotel booking services on the service platform; the service functions provided by the target AI service program to users include calculating the points that the user can obtain after consuming the hotel booking service; the method includes:

[0007] Obtain the hotel booking service-related demand data entered by the user in the visual interface corresponding to the target artificial intelligence service program;

[0008] The demand data is semantically recognized, and the user's consumption demand for the hotel booking service is determined based on the semantic recognition results; wherein, the consumption demand includes the consumption demand used to trigger the calculation of points that the user can obtain after consuming the hotel booking service.

[0009] In response to the determined consumption demand of the user for the hotel booking service, based on the basic information obtained from the hotel brand for calculating the user's rights, the number of points that the user can obtain after consuming services corresponding to the consumption demand for the hotel booking service is calculated.

[0010] Optionally, the basic information includes: the points allocation rules corresponding to the hotel brand; and the user's rights level for the hotel booking service, for which the hotel brand has authorized data access.

[0011] Based on the aforementioned basic information, the calculation of the number of points a user can earn after consuming services corresponding to their consumption needs in the hotel booking service includes:

[0012] The number of points allocated to a user's rights level is determined based on the user rights rules.

[0013] Using the allocated points as the base allocation, the actual number of points a user can earn after consuming the hotel booking service is further calculated.

[0014] Optionally, the service platform also deploys a basic artificial intelligence service program based on LLM, corresponding to the service platform;

[0015] Obtain user input request data, including:

[0016] The system obtains user-inputted demand data distributed by the basic artificial intelligence service program corresponding to the service platform; wherein, the demand data is initially semantically recognized by the basic artificial intelligence service, and after determining that the demand data corresponds to the hotel brand based on the semantic recognition result, it is distributed to the target artificial intelligence service program.

[0017] Optionally, the points allocation quantity is used as the base allocation quantity to further calculate the actual number of points that the user can obtain after consuming the hotel booking service, including:

[0018] Obtain operational information for the hotel booking service provided by the merchant corresponding to the hotel booking service; wherein, the operational information includes the additional number of points that a user can obtain after consuming the hotel booking service;

[0019] The points allocation quantity is used as the base allocation quantity, and added to the additional quantity to obtain the actual number of points that the user can obtain after consuming services corresponding to the consumption needs for the hotel booking service.

[0020] Optionally, the consumption demand includes the consumption demand for recommending hotel booking services to users;

[0021] Before using the allocated points as the base allocation and further calculating the actual number of points a user can earn after consuming services related to the hotel booking service, the process also includes:

[0022] The system outputs at least one recommendation strategy to the user through a visual interface corresponding to the target service program; wherein the recommendation strategy indicates the conditions that the actual number of points the user can obtain after consuming the service must meet.

[0023] Obtain the target recommendation strategy selected by the user from the at least one recommendation strategy;

[0024] Using the allocated points as the base allocation, the actual number of points a user can earn after consuming services related to the hotel booking service is further calculated, including:

[0025] In response to the target recommendation strategy selected by the user from the at least one recommendation strategy, the number of points allocated is used as the base allocation number to further calculate the actual number of points that the user can obtain after consuming services for all hotel booking services released by the hotel brand.

[0026] In response to the calculated actual number of points a user can earn after consuming services for all the hotel booking services, N hotel booking services are further selected from all the hotel booking services whose actual number of points a user can earn after consuming services satisfies the conditions indicated by the target recommendation strategy; wherein, N is a preset threshold.

[0027] The N hotel booking services are displayed to the user through the visual interface.

[0028] Optionally, the consumption demand includes the consumption demand for calculating the actual number of points a user can earn after consuming services at a specified target hotel booking service;

[0029] Before using the allocated points as the base allocation and further calculating the actual number of points a user can earn after consuming services related to the hotel booking service, the process also includes:

[0030] The system interacts with the user through a visual interface corresponding to the target service program to obtain the user's input of the specified target hotel booking service.

[0031] Using the allocated points as the base allocation, the actual number of points a user can earn after consuming services related to the hotel booking service is further calculated, including:

[0032] In response to the obtained target hotel booking service, the points allocation quantity is used as the base allocation quantity to further calculate the actual number of points that the user can obtain after consuming the service for the target hotel booking service;

[0033] The actual number of points a user can earn after consuming the service for the target hotel booking will be displayed to the user through the visualization interface.

[0034] Optionally, the consumption demand includes a request to recommend to the user the actual number of points earned after consuming services, and a hotel booking service package that ensures the user's benefit level does not decline.

[0035] Before using the allocated points as the base allocation and further calculating the actual number of points a user can earn after consuming services related to the hotel booking service, the process also includes:

[0036] The system outputs at least one recommendation strategy to the user through a visual interface corresponding to the target service program; wherein the recommendation strategy indicates the conditions that the user can meet for the actual number of points that can be obtained after consuming the hotel booking service in the hotel booking service package.

[0037] Obtain the target recommendation strategy selected by the user from the at least one recommendation strategy;

[0038] Using the allocated points as the base allocation, the actual number of points a user can earn after consuming services related to the hotel booking service is further calculated, including:

[0039] In response to the target recommendation strategy selected by the user from the at least one recommendation strategy, the number of points allocated is used as the base allocation number to further calculate the actual number of points that the user can obtain after consuming services for all hotel booking services released by the hotel brand.

[0040] In response to the calculated actual number of points a user could earn after consuming services for all the hotel booking services, the system further filters hotel booking service combinations for the user from all the hotel booking services and generates a consumption strategy for the user for the hotel booking service combinations; wherein, the consumption strategy is a consumption strategy that ensures the user's benefit level does not decline based on the actual number of points earned by the user after consuming services for the hotel booking services in the hotel booking service combinations; and the earned points satisfy the conditions indicated by the target level preservation strategy.

[0041] The hotel booking service package and the consumption strategy are displayed to the user through the visual interface.

[0042] Optionally, the consumption demand includes a request to recommend to the user the actual number of points earned after consuming services, and a hotel booking service package that can ensure the user's benefit level is upgraded.

[0043] Before using the allocated points as the base allocation and further calculating the actual number of points a user can earn after consuming services related to the hotel booking service, the process also includes:

[0044] The system outputs at least one recommendation strategy to the user through a visual interface corresponding to the target service program; wherein the recommendation strategy indicates the conditions that the user can meet for the actual number of points that can be obtained after consuming the hotel booking service in the hotel booking service package.

[0045] Obtain the target recommendation strategy selected by the user from the at least one recommendation strategy;

[0046] Using the allocated points as the base allocation, the actual number of points a user can earn after consuming services related to the hotel booking service is further calculated, including:

[0047] In response to the target recommendation strategy selected by the user from the at least one recommendation strategy, the number of points allocated is used as the base allocation number to further calculate the actual number of points that the user can obtain after consuming services for all hotel booking services released by the hotel brand.

[0048] In response to the calculated actual number of points a user could earn after consuming services for all the hotel booking services, the system further filters hotel booking service combinations for the user from all the hotel booking services and generates a consumption strategy for the user for the hotel booking service combinations; wherein, the consumption strategy is a consumption strategy that ensures that the actual number of points the user earns after consuming services for hotel booking services in the hotel booking service combinations can ensure that the user's benefit level increases; and, the points earned meet the conditions indicated by the target level maintenance strategy.

[0049] The hotel booking service package and the consumption strategy are displayed to the user through the visual interface.

[0050] Optionally, the at least one recommended strategy includes any or a combination of the following:

[0051] The user can actually obtain the maximum number of points;

[0052] The lowest discounted price corresponding to the hotel booking service is calculated based on the actual number of points that the user can obtain.

[0053] The highest recommendation weight value is calculated by weighting the actual number of points a user can obtain with the discount price calculated based on the actual number of points a user can obtain; the recommendation weight value is positively correlated with the actual number of points and the discount price.

[0054] Optionally, the points may include monetized points;

[0055] Calculating the discounted price corresponding to the hotel booking service includes:

[0056] Based on the exchange relationship between the monetized points and the designated currency, calculate the amount of the designated currency that the user can exchange for the actual number of points they can obtain.

[0057] Based on the calculated amount of the specified currency, a discount price corresponding to the hotel booking service is further calculated.

[0058] Optionally, the artificial intelligence service program includes an intelligent agent built on an LLM basis.

[0059] This specification also proposes a user rights calculation method, applied to a target artificial intelligence service program deployed on a service platform corresponding to a service provider; wherein, the target artificial intelligence service program is a service program built based on LLM; the service provider publishes online services on the service platform; the service functions provided by the target service program to users include calculating the user rights that the user can obtain after consuming the online service; the method includes:

[0060] Obtain user input data;

[0061] The demand data is semantically identified, and the user's consumption demand for the online service is determined based on the semantic identification results; wherein, the consumption demand includes the consumption demand used to trigger the calculation of user rights that the user can obtain after consuming the online service;

[0062] In response to the determined consumption demand of the user for the online service, based on the basic information obtained from the service provider for calculating the user's rights, the user rights that the user can obtain after consuming services corresponding to the consumption demand for the online service are calculated.

[0063] In the above embodiments, on the one hand, by opening up the computing power of LLM deployed on the service platform to the service provider, deploying an artificial intelligence service program (such as an LLM agent) based on LLM corresponding to the service provider on the service platform, and authorizing the basic information used to calculate user rights to the artificial intelligence service program, users can use the artificial intelligence service program to efficiently calculate the user rights they can obtain after consuming the online services published by the service provider on the service platform. This can improve the accuracy of the calculated user rights and significantly reduce the operational difficulty for users when calculating user rights.

[0064] On the other hand, in the application scenario of calculating points that users can earn after consuming hotel booking services on e-commerce platforms (such as online travel platforms), the computing power of LLM deployed on the e-commerce platform can be opened to hotel brands. An AI service program based on LLM, corresponding to the hotel brand, can be deployed on the service platform. The hotel brand can then authorize this AI service program with basic information used for calculating points (such as points allocation rules and the user's privilege level within the hotel brand). This allows users to efficiently calculate the points they can earn after consuming hotel booking services offered by the hotel brand on the e-commerce platform, thereby improving the accuracy of the calculated points and significantly reducing the operational difficulty for users when calculating points.

[0065] Thirdly, in the application scenario of recommending hotel booking services to users, by opening up the computing power of LLM deployed on the e-commerce platform to hotel brands, deploying an AI service program based on LLM corresponding to the hotel brands on the service platform, and authorizing the basic information used to calculate points to the AI ​​service program, users can use the AI ​​service program to efficiently query the actual number of points that can be obtained after consuming services and hotel service combinations that meet the conditions specified by the user, and significantly reduce the difficulty of users' operation when searching for hotels.

[0066] Fourthly, in the application scenario of accurately calculating the user benefits that users can obtain after consuming services for designated hotel booking products on e-commerce platforms, the computing power of LLM deployed on the e-commerce platform is opened to hotel brands. An AI service program based on LLM corresponding to the hotel brand is deployed on the service platform, and the hotel brand authorizes the basic information used to calculate points to the AI ​​service program. This allows users to use the AI ​​service program to accurately calculate the points they can obtain after consuming services for designated hotel booking products on e-commerce platforms, and significantly reduces the difficulty for users when calculating points.

[0067] Fourthly, in application scenarios involving maintaining or upgrading users' privilege levels with hotel brands, the computing power of LLM deployed on the e-commerce platform is opened to hotel brands. An AI service program based on LLM, corresponding to the hotel brand, is deployed on the service platform. The hotel brand authorizes this AI service program with the basic information used to calculate points. This allows users to efficiently query the actual number of points they can earn after consuming services, ensuring that their privilege level does not decrease or increases, and meeting the hotel service combinations specified by the user. This significantly reduces the difficulty for users in maintaining or upgrading their privilege levels. Attached Figure Description

[0068] To more clearly illustrate the technical solutions of the embodiments in this specification, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0069] Figure 1 This is a schematic diagram of the architecture of an Internet service system shown in one embodiment of this specification;

[0070] Figure 2This is a flowchart illustrating a user rights calculation method in one embodiment of this specification;

[0071] Figure 3 This is a flowchart illustrating a method for calculating user rights for hotel booking services in one embodiment of this specification;

[0072] Figure 4 This is a schematic diagram illustrating the deployment of an LLM agent on an OTP platform in one embodiment of this specification;

[0073] Figure 5 This is a schematic diagram illustrating a user-facing visual interface provided by a dedicated agent in one embodiment of this specification;

[0074] Figure 6 This is a schematic diagram illustrating a specific agent recommending hotels to a user, as shown in one embodiment of this specification.

[0075] Figure 7 This is a schematic diagram illustrating a dedicated agent performing hotel actuarial calculations for a user-specified hotel in one embodiment of this specification;

[0076] Figure 8 This is a schematic diagram illustrating a strategy for a dedicated agent to maintain a user's membership card level, as shown in one embodiment of this specification.

[0077] Figure 9 This is a schematic diagram illustrating a dedicated agent's strategy for developing a membership card upgrade plan for a user, as shown in one embodiment of this specification.

[0078] Figure 10 This is a schematic structural diagram of an electronic device shown in one embodiment of this specification;

[0079] Figure 11 This is a block diagram of a user rights calculation device shown in one embodiment of this specification;

[0080] Figure 12 This is a block diagram of another user rights calculation device shown in one embodiment of this specification. Detailed Implementation

[0081] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with one or more embodiments of this specification. Rather, they are merely examples of apparatuses and methods consistent with some aspects of one or more embodiments of this specification as detailed in the appended claims.

[0082] It should be noted that the steps of the corresponding methods are not necessarily performed in the order shown and described in this specification in other embodiments. In some other embodiments, the methods may include more or fewer steps than described in this specification. Furthermore, a single step described in this specification may be broken down into multiple steps in other embodiments; and multiple steps described in this specification may be combined into a single step in other embodiments.

[0083] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this manual are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0084] This specification aims to propose a technical solution that utilizes a service program built on an LLM (Large Language Model) to assist users in quickly and accurately calculating the user rights they can obtain after consuming online services published on a service platform.

[0085] Especially in scenarios where users calculate the user benefits (such as points) they can obtain after consuming services (such as hotel bookings) on e-commerce platforms (such as online travel platforms), this specification also proposes a technical solution that utilizes an artificial intelligence service program (such as an LLM agent) built on LLM to assist users in quickly and accurately calculating the user benefits they can obtain after consuming services for goods, thereby improving the accuracy of the calculated user benefits and reducing the operational difficulty for users when calculating user benefits.

[0086] Figure 1 This is a schematic diagram of the architecture of an Internet service system provided in an exemplary embodiment. For example... Figure 1 As shown, the system may include a server 11, a network 12, and several electronic devices, such as a PC (Personal Computer) 13, a mobile phone 14, etc.

[0087] Server 11 can be a physical server containing an independent host, or it can be a virtual server hosted in a host cluster. During operation, server 11 can run server-side programs for a certain application to implement the relevant functions of that application. For example, when server 11 runs a program for a certain Internet service, it can function as a corresponding Internet service platform.

[0088] PC13 and mobile phone14 are just some of the types of electronic devices that users can use. In reality, users can obviously also use electronic devices such as tablets, laptops, PDAs (Personal Digital Assistants), wearable devices (such as smart glasses, smartwatches, etc.), etc., and one or more embodiments in this specification do not limit this. During operation, the electronic device can run a client-side program of an application to implement the relevant functions of that application. For example, when the electronic device runs a program for an internet service, it can act as a client for that internet service. The aforementioned internet service client application can be launched and run on the electronic device. This client-side program can be a native application installed on the electronic device, or it can be a mini-program, quick app, or other similar form.

[0089] Of course, when using web technologies such as HTML5 or similar, the relevant functions can be achieved through the page displayed by the browser. The browser here can be a standalone browser application or a browser module embedded in some applications.

[0090] As for the network 12 that enables interaction between electronic devices such as PC13 and mobile phone 14 and server 11, communication can be achieved using either wired or wireless networks, depending on the communication methods supported by the respective electronic devices. This specification does not impose any restrictions on this. For example, PC13 can support both wired and wireless communication, so it can use either wired or wireless networks as needed. Mobile phone 14 typically only supports wireless communication, so it can use a wireless network for communication.

[0091] It should be noted that the aforementioned internet services may include any service implemented on the internet; for example, the aforementioned internet services may specifically include calculation services for user rights obtained after consuming services related to goods published on e-commerce platforms, online operation services for online operation of goods published on e-commerce platforms, travel transaction services for travel-related products (such as air tickets), fresh food transaction services, or other types of services, etc., but this specification does not impose any restrictions on this.

[0092] The technical solution of this specification will be described in detail below with reference to the accompanying drawings.

[0093] Please see Figure 2 , Figure 2This document presents a flowchart illustrating a method for calculating user rights, applied to a target artificial intelligence service program (hereinafter referred to as the target service program) deployed on a service platform corresponding to a service provider; wherein, the target service program is a service program built based on LLM; the service provider publishes online services on the service platform; the service functions provided by the target service program to users include calculating the user rights that the user can obtain after consuming the online service, including the following execution process:

[0094] Step 202: Obtain user-inputted requirement data;

[0095] The aforementioned service programs built on LLM can specifically include any form of application that uses LLM as the core computing engine and is responsible for providing natural language understanding, generation, reasoning, and decision-making capabilities.

[0096] For example, in some embodiments, the aforementioned service program built on LLM may specifically include an agent built on LLM. The agent can use LLM as a core component to autonomously perform tasks and make decisions in a specific environment.

[0097] The aforementioned online services may include any form of online service, and are not specifically limited in this specification.

[0098] For example, in some embodiments, the online services mentioned above may specifically include product-related services published by the service provider on the service platform.

[0099] The goods published by the service provider on the service platform can include any form of physical or virtual goods, and this specification will not impose any special restrictions on them.

[0100] For example, in some embodiments, the aforementioned service platform may specifically include e-commerce platforms such as OTP (Online Travel Platform) or OTA (Online Travel Agency); in this case, the aforementioned goods may specifically include online travel products (such as tickets, hotel bookings, etc.) published by merchants on these platforms. The aforementioned service providers may specifically include merchants or brands of online travel products.

[0101] In practical applications, the computing power of LLM deployed on the service platform can be opened up to the service provider, so that the service provider can deploy target service programs based on LLM on the service platform according to specific operation and management needs.

[0102] For example, taking the aforementioned service program built on LLM, specifically an intelligent agent built on LLM, the service platform can grant the service provider the permission to deploy intelligent agents built on LLM on the platform. This allows the service provider to deploy its own intelligent agent on the service platform based on specific needs, and to operate the intelligent agent autonomously based on the user data it possesses, in order to provide relevant intelligent services to users.

[0103] It should be noted that the target service program deployed on the service platform corresponding to the aforementioned service providers can specifically refer to a dedicated service program built for a specific service provider based on the LLM deployed on the service platform, or a service program built for multiple service providers and shared by those multiple service providers. In other words, in practical applications, a service program built on an LLM deployed on the service platform can correspond to a single service provider or multiple service providers. For example, taking the aforementioned service program as an intelligent agent built on an LLM as an example, in one case, this intelligent agent can be a dedicated intelligent agent corresponding to a specific service provider, or an intelligent agent shared by multiple service providers.

[0104] The aforementioned target service program deployed on the service platform can specifically provide users with multiple service functions, which may include calculating the user rights that a user can obtain after consuming online services published by the service provider on the service platform.

[0105] The aforementioned user rights may specifically include any type of rights issued by the service provider to users who have consumed the online services it provides for business purposes, and will not be specifically limited in this specification;

[0106] For example, in one instance, the aforementioned user rights may specifically include rights certificates; in this case, the service provider may issue a certain number of rights certificates to users who have consumed the online services it provides, as user rights.

[0107] In another example, the aforementioned user benefits may specifically include a discounted price (also known as a rebate price) calculated based on the actual number of benefit tokens a user can obtain after consuming the online service. In this case, the service provider can calculate the aforementioned discounted price for users who have consumed the online service offered by it, as a user benefit.

[0108] Of course, in practical applications, the aforementioned user rights can also be a combination of rights certificates and the aforementioned discounted price. In this case, in addition to issuing a certain number of rights certificates to users who have consumed the online services offered by the service provider, the service provider can also calculate a discounted price corresponding to the online service based on the actual number of rights certificates issued to the user, which can also be considered as a user right.

[0109] For example, taking the aforementioned online service as a hotel booking service, the service provider may include the merchant or brand corresponding to the hotel booking service, and the user rights may include the points that the user can obtain after consuming the hotel booking service, as well as the discount price corresponding to the hotel booking service calculated based on the actual number of points that the user can obtain after consuming the hotel booking service.

[0110] The aforementioned demand data may specifically include any form of demand information input by the user that corresponds to the service functions provided to the user by the aforementioned service program;

[0111] For example, in some embodiments, the aforementioned requirement data may specifically include operation instructions in text form. Of course, in some cases, if the LLM used to construct the aforementioned target service program is a multimodal LLM, the requirement data input by the user may also be data in other modalities besides text data; for example, audio data, image data, etc.

[0112] In practical applications, the client corresponding to the aforementioned target service program can provide users with a visual interface for interacting with the target service program. In this case, when a user needs to use a specific service function provided by the target service program, they can input the required data corresponding to that service function in the visual interface.

[0113] The aforementioned client can further submit the user-inputted request data to the aforementioned target service program for further processing.

[0114] In practical applications, the client can either directly submit the user-inputted operation information to the target service program, or first send the user-inputted operation information to the service platform corresponding to the online service, which will then distribute it to the target service program.

[0115] In some embodiments, a basic AI service program (hereinafter referred to as the basic service program) based on LLM, corresponding to the service platform, can also be deployed on the service platform. In this case, the user can input requirement data in a visual interface provided by the client corresponding to the basic service program, and the client can further submit the user-input requirement data to the basic service program.

[0116] After obtaining the aforementioned requirement data input by the user, the basic service program can perform preliminary semantic recognition on the requirement data. Based on the semantic recognition results, after determining that the requirement data corresponds to a specific service provider, the requirement data can be further distributed to the target service program deployed by the service provider on the service platform.

[0117] For example, after the basic service program determines, based on the preliminary semantic recognition results, that the demand data matches the service functions that can be provided by a specific service provider's target service program (such as discovering that the user wants to consume online services published by a specific service provider or has other needs), the demand data can be further distributed to the aforementioned target service program deployed by the service provider on the service platform.

[0118] In this way, basic service programs corresponding to the service platform and target service programs corresponding to each service provider can be deployed on the service platform. Based on these two types of service programs, a two-level service system is formed to provide intelligent services to users. After a user submits a request to the basic service program corresponding to the service platform, the basic service program can further distribute the request after confirming that the user's submitted request matches the service function provided by the target service program deployed by a specific service provider. This allows for the provision of more diverse service functions to users.

[0119] In some embodiments, when the target service program obtains the user's input request data, it may specifically interact with the user in a multi-turn session manner, and then obtain the user's input request data during the interaction process.

[0120] For example, in practical applications, the LLM used to construct the aforementioned service program can specifically be an LLM service model obtained by fine-tuning and training a basic LLM model. The training samples used for fine-tuning and training the basic LLM model can specifically be training samples built upon a knowledge base authorized by the service provider. These training samples can specifically include multi-turn session data samples generated during the calculation of user rights obtained after a user initiates service consumption for the aforementioned online service. The knowledge base authorized by the service provider can specifically include any form of data generated by the service provider during the operation of the online service published on the service platform.

[0121] In this way, not only can an LLM service model be obtained through fine-tuning training that adapts to the consumption needs of the aforementioned service providers, but the fine-tuned LLM service model can also support multi-turn conversations for interaction with users. In other words, through model fine-tuning, the LLM service model already has the ability to interact with users using multi-turn conversations.

[0122] In this scenario, the aforementioned target service program can further interact with the user through a visual interface provided by the aforementioned client, using a multi-turn session approach, to collect the user's input request data during the interaction process.

[0123] It should be noted that the specific method by which users input their required data through multi-round sessions with the aforementioned target service program is not specifically limited in this specification. In practical applications, the design can be flexibly adapted based on specific needs.

[0124] For example, in practical applications, the aforementioned target service program can instruct users to supplement missing requirement data by asking further questions. Alternatively, during the interaction process, it can output some interactive components in the visual interface for visual interaction with users, allowing users to interact with these components (such as clicking) to select the required requirement data from at least one preset requirement data that users can choose from, or to confirm the requirement data that has already been entered.

[0125] Step 204: Perform semantic recognition on the demand data based on the LLM, and determine the user's consumption demand for the online service based on the semantic recognition result; wherein, the consumption demand includes consumption demand for triggering the calculation of user rights that the user can obtain after consuming the online service;

[0126] After obtaining the user's input demand data, the aforementioned target service program can perform semantic recognition on the demand data based on the semantic recognition capability of LLM, and determine the user's consumption demand for the online services published by the aforementioned service provider based on the semantic recognition results.

[0127] Specifically, the aforementioned consumption demand may include consumption demand used to trigger the calculation of user rights that a user can obtain after consuming the online service.

[0128] It should be noted that, in practical applications, the aforementioned consumption demand can specifically cover any form of consumption demand used to trigger the calculation of user rights that a user can obtain after consuming the online service, and will not be specifically limited in this specification.

[0129] For example, in practical applications, the following consumption demands may trigger the calculation of user benefits that a user can obtain after consuming the online service:

[0130] Recommend to users the amount of user benefits that users can obtain after consuming services to meet the consumption needs of online services based on user-defined target conditions;

[0131] Calculate the consumption demand for user benefits that a user can obtain after consuming specified online services;

[0132] Recommend online service combinations to users that will not lower their privilege level after they consume services;

[0133] Recommending online service packages to users that will elevate their privilege level after they consume services;

[0134] Recommend services to users in a way that ensures their privilege level does not decrease after consuming services, and that the privileges they receive meet their consumption needs for a combination of online services based on the target conditions specified by the user.

[0135] Recommend services to users that will increase their privilege level after they consume services, and the privileges they can obtain will meet their consumption needs for a combination of online services based on the target conditions specified by the user.

[0136] Step 206: In response to the determined consumption demand of the user for the online service, based on the basic information obtained from the service provider for calculating the user's rights, calculate the user rights that the user can obtain after consuming the service corresponding to the consumption demand for the online service.

[0137] Once the aforementioned target service program determines the user's consumption needs for the online services published by the aforementioned service provider, it can then obtain basic information from the service provider to calculate the user's rights in response to the determined user's consumption needs for the online services; and then calculate the user's rights that the user can obtain after consuming the online services corresponding to the consumption needs based on the basic information.

[0138] It should be noted that at least some of the basic information mentioned above may be information for which the service provider has authorized data access.

[0139] In some implementations, the aforementioned basic information may specifically include user rights allocation rules corresponding to the online service; and the rights level of users who have been authorized by the service provider for the online service; wherein, the user rights allocation rules may specifically include the correspondence between multiple preset rights levels and the user rights allocation quantity set for each of the multiple rights levels; that is, by querying the correspondence, the user rights allocation quantity corresponding to the user's rights level for the online service can be determined, and then user rights can be allocated to the user based on the user rights allocation quantity.

[0140] In this scenario, when calculating the user rights that a user can obtain after consuming services corresponding to the aforementioned consumption needs in relation to the online service, the target service program can first obtain the user rights allocation rules corresponding to the online service from the service provider; and the user's rights level for the online service. Then, based on the obtained user rights rules, it can determine the amount of user rights allocated corresponding to the user's rights level for the online service. Finally, it can use this amount of user rights allocated as the base amount of user rights allocated to the user after consuming services in relation to the online service, and further calculate the actual amount of user rights that the user can obtain after consuming services in relation to the online service.

[0141] In some embodiments, when the target service program uses the allocated user rights as the base amount of user rights allocated to the user after the user consumes the online service, and further calculates the actual amount of user rights the user can obtain after consuming the online service, it may further allocate an additional amount of user rights to the user on top of this base amount. The specific amount of additional user rights allocated to the user may depend on the actual operational needs of the service provider in operating the online service, and in practice, it can be flexibly determined based on actual operational needs.

[0142] In some embodiments, when the target service program uses the allocated user rights quantity as the base quantity of user rights allocated to the user after the user consumes the online service, and further calculates the actual quantity of user rights that the user can obtain after consuming the online service in accordance with the consumption demand, it can first obtain the operation information for the online service provided by the operator corresponding to the online service. This operation information can specifically include an additional quantity of user rights that the user can obtain after consuming the online service. Then, the allocated user rights quantity can be used as the base quantity of user rights allocated to the user after consuming the online service, and added to the additional quantity to obtain the actual quantity of user rights that the user can obtain after consuming the online service in accordance with the consumption demand.

[0143] Specifically, the aforementioned operator can be a third party that has a cooperative relationship with the aforementioned service provider and operates the online services published by the service provider on the aforementioned service platform. The aforementioned operational information can specifically include any form of operational information concerning the aforementioned online services generated by the aforementioned operator in the process of operating and managing the online services published by the service provider on the aforementioned service platform.

[0144] For example, taking the service provider as an online service brand, the operator could be a merchant with a cooperative relationship with that brand. This merchant can manage and operate the online services published by the service provider on the service platform. The operational information could specifically include promotional information initiated by the merchant during the operation of the online service.

[0145] For example, taking the aforementioned online service as a hotel booking service, the user benefits could be points earned by the user after consuming hotel booking services from a particular brand. The user's benefit level for this online service could specifically be the actual membership level of the user's personal membership card activated by that brand. Different membership levels could result in different points earned after consuming hotel booking services; for example, a higher membership level would yield more points. The aforementioned operator could specifically be a merchant at a hotel location that has a cooperative relationship with the brand. The aforementioned operational information could specifically be promotional information related to promotional activities for hotel booking services initiated by the hotel location merchant for business purposes. Examples include brand flash sales, activity challenges, and in-store preferential policies, etc.

[0146] In this case, when the aforementioned target service program further calculates the actual amount of user benefits that the user can obtain after consuming the hotel booking service, it can first obtain the points allocation rules authorized by the brand owner corresponding to the hotel booking service; and the membership level information of the user's activated membership card; and then determine the number of points allocated corresponding to the user's membership card level based on the obtained points allocation rules.

[0147] In addition, the aforementioned target service program can also obtain promotional information related to the promotional activities of the hotel stores corresponding to the hotel booking service, and determine the additional number of points allocated to the user by the hotel stores in the promotional activities based on the promotional information. Then, the number of points allocated to the user's membership card level can be added to the above-mentioned additional number to obtain the actual number of points that the user can obtain after consuming the hotel booking service.

[0148] In this way, the aforementioned target service program can simultaneously calculate user rights based on the basic information of data authorization provided by the service provider and the operational information provided by the operator of the aforementioned online service, thereby improving the accuracy of the calculated user rights.

[0149] For example, taking the aforementioned online service as a hotel booking service and the user benefits as points, if the points a user can earn after consuming the hotel service are calculated solely based on data authorization from the hotel booking service brand, the calculated number of points might be inaccurate because promotional activities initiated by the hotel stores themselves are not taken into account. However, if the calculation of points is based on promotional information provided by specific stores, the accuracy of the calculated points will obviously be improved.

[0150] It should be noted that in practical applications, since the aforementioned consumption demand can specifically cover any form of consumption demand used to trigger the calculation of user rights that a user can obtain after consuming the online service, in practical applications, when the target service program processes the aforementioned consumption demand, in addition to calculating the actual amount of user rights that a user can obtain after consuming the online service corresponding to the consumption demand, it may also need to execute some other processing logic under different user consumption demands.

[0151] In some embodiments, the aforementioned consumption demand may specifically include the consumption demand for online services that recommend to users the actual amount of user benefits that users can obtain after consuming services, which meets the target conditions specified by the user; for example, taking the aforementioned online service as a hotel booking service and the aforementioned user benefits as points as an example, the consumption demand may specifically be the service demand of "recommending the most cost-effective points hotels to users".

[0152] In this case, the aforementioned target service program can respond to the determined consumption demand of the user for the aforementioned online service by outputting at least one recommendation strategy for the user to choose from through a visual interface corresponding to the aforementioned target service program; wherein, these recommendation strategies indicate the target conditions that the actual number of points that the user can obtain after consuming the service satisfies.

[0153] Once a user selects a target recommendation strategy from these recommendation strategies, the target service program can respond to the user's selection of the target recommendation strategy from at least one of the above recommendation strategies, further obtain the aforementioned basic information, and based on this basic information, further calculate the actual amount of user rights that the user can obtain after consuming all online services published by the service provider.

[0154] Once the target service program calculates the actual amount of user benefits that a user can obtain after consuming services in all of the above online services, it can further select N online services from all of the above online services whose actual amount of user benefits that a user can obtain after consuming services satisfies the target conditions indicated by the above target recommendation strategy.

[0155] Here, N is a preset threshold. In practical applications, the value of N can be flexibly set and modified by the user. Then, the selected N online services can be displayed to the user through the visual interface provided by the target service program.

[0156] In some embodiments, the aforementioned consumption demand may specifically include the consumption demand for calculating the actual amount of user benefits that a user can obtain after consuming services in a specified online service; for example, taking the aforementioned online service as a hotel booking service and the aforementioned user benefits as points as an example, the consumption demand may specifically be the service demand of "calculating the points that a user can obtain after staying at a specific hotel".

[0157] In this case, the aforementioned target service program can respond to the determined consumption demand of the user for the aforementioned online service by interacting with the user through a visual interface corresponding to the aforementioned target service program, and obtain the specified target online service input by the user;

[0158] After a user inputs their desired online service, the target service program can respond to the obtained target online service, further obtain the aforementioned basic information, and based on the basic information, further calculate the actual amount of user benefits that the user can obtain after consuming the service for the target hotel booking service.

[0159] Once the target service program calculates the actual amount of user benefits that a user can obtain after consuming the aforementioned target online service, it can output and display this actual amount of user benefits to the user through the aforementioned visualization interface.

[0160] In some embodiments, the aforementioned consumption demand may further include the consumption demand of recommending online service combinations to users so that the user's membership level does not decrease after consuming services; for example, taking the aforementioned online service as a hotel booking service and the aforementioned user benefits as points as an example, the consumption demand may specifically be the service demand of "recommending a stay combination strategy to users to ensure that the user's membership card membership level does not decrease".

[0161] In this case, the aforementioned target service program can respond to the determined user's consumption demand for the aforementioned online services by outputting at least one recommendation strategy for the user to choose from through a visual interface corresponding to the aforementioned target service program; wherein, the recommendation strategy indicates the conditions that the actual number of points the user can obtain after consuming the online services in the aforementioned online service combination must meet.

[0162] Once a user selects a target recommendation strategy from these recommendation strategies, the target service program can respond to the user's selection of the target recommendation strategy from at least one of the above recommendation strategies, further obtain the aforementioned basic information, and based on this basic information, further calculate the actual amount of user rights that the user can obtain after consuming all online services published by the service provider.

[0163] Once the target service program calculates the actual amount of user benefits a user can obtain after consuming services across all the aforementioned online services, it further filters online service combinations for the user and generates a consumption strategy for those combinations. This consumption strategy ensures that the user's benefit level does not decline, based on the actual number of points earned after consuming services within the chosen online service combination, and that the earned points meet the target conditions indicated by the benefit level maintenance strategy. The target service program then displays the generated online service combinations and consumption strategies to the user through the aforementioned visual interface.

[0164] It should be noted that the method by which a user downgrades their privilege level for the aforementioned online services usually depends on the specific needs of the service provider for operating the online service. The downgrade methods for different online services published by different service providers, or even different online services published by the same service provider, may be the same or may differ. This specification will not specify any further details.

[0165] For example, taking the aforementioned online service as a hotel booking service, the user's membership level can be the actual membership level of the personal membership card opened by the user for a certain hotel brand. In this scenario, each membership level of the user's membership card can be pre-bound to the minimum number of stays for the hotel booking service of that brand within a membership evaluation cycle (such as one year). Once the number of stays for the hotel booking service of that brand within the membership evaluation cycle is lower than the minimum number bound to the current membership level, the user's membership level can be downgraded.

[0166] In this context, when the aforementioned target service program selects online service combinations for a user and generates a consumption strategy for that online service combination, it can specifically plan a combination of hotel booking services for the user to check in, and generate a check-in strategy for the user that ensures the number of check-ins for the hotel services in that combination reaches the minimum number of check-ins tied to the current membership level within the current membership evaluation period.

[0167] In some embodiments, the aforementioned consumption demand may further include the consumption demand of recommending online service combinations to users that will increase the user's benefit level after the user consumes the service; for example, taking the aforementioned online service as a hotel booking service and the aforementioned user benefit as points as an example, the consumption demand may specifically be the service demand of "recommending a stay combination strategy to users that ensures that the user's membership card can be upgraded".

[0168] In this case, the aforementioned target service program can respond to the determined user's consumption demand for the aforementioned online services by outputting at least one recommendation strategy for the user to choose from through a visual interface corresponding to the aforementioned target service program; wherein, the recommendation strategy indicates the conditions that the actual number of points the user can obtain after consuming the online services in the aforementioned online service combination must meet.

[0169] Once a user selects a target recommendation strategy from these recommendation strategies, the target service program can respond to the user's selection of the target recommendation strategy from at least one of the above recommendation strategies, further obtain the aforementioned basic information, and based on this basic information, further calculate the actual amount of user rights that the user can obtain after consuming all online services published by the service provider.

[0170] Once the target service program calculates the actual amount of user benefits a user can obtain after consuming services across all the aforementioned online services, it further filters online service combinations for the user and generates a consumption strategy for those combinations. This consumption strategy ensures that the user's benefit level does not decline, based on the actual number of points earned after consuming services within the chosen online service combination, and that the earned points meet the target conditions indicated by the benefit level maintenance strategy. The target service program then displays the generated online service combinations and consumption strategies to the user through the aforementioned visual interface.

[0171] It should be noted that the way users upgrade their rights level for the aforementioned online services usually depends on the specific needs of the service provider for operating the online service. The way users downgrade their rights level may be the same for different service providers, or even for different online services published by the same service provider. This specification will not make specific limitations.

[0172] For example, taking the aforementioned online service as a hotel booking service, the user's benefit level can be the actual membership level of the personal membership card opened by the user for a certain hotel brand. In one scenario, each membership level of the user's membership card can be pre-bound to the maximum number of stays for the hotel booking service of that brand within a membership evaluation cycle (such as within one year). Once the number of stays for the hotel booking service of that brand within the membership evaluation cycle reaches the maximum number bound to the current membership level, the user's membership level can be upgraded.

[0173] In this context, when the aforementioned target service program selects online service combinations for a user and generates a consumption strategy for that online service combination, it can specifically plan a combination of hotel booking services for the user to check in, and generate a check-in strategy for the user that ensures the user's check-in frequency within the current membership evaluation period reaches the maximum number of check-ins tied to the current membership level.

[0174] It should be noted that the target conditions specified by the user can be flexibly specified by the user based on specific needs, and will not be specifically limited in this specification.

[0175] For example, in practical applications, during the process of multi-round conversational interaction between the target service program and the user through the visual interface provided by the client, the program can output several selectable conditions to the user through the visual interface, so that the user can select the required conditions as the target conditions during the interaction.

[0176] In some embodiments, if the aforementioned user rights are rights certificates, the target conditions specified by the user for those user rights may specifically include maximizing the actual number of rights certificates that can be obtained; correspondingly, the aforementioned consumption demand may specifically include the consumption demand of recommending online services that maximize the actual number of user rights that the user can obtain after consuming the service.

[0177] In this scenario, the aforementioned target service program, in addition to calculating the actual number of user rights a user can obtain after consuming all online services published by the service provider on the service platform, can further select the N online services from all the online services published by the service provider on the service platform that offer the highest number of user rights after consumption. Then, these N selected online services can be displayed to the user through the visual interface provided by the target service program.

[0178] In some embodiments, if the aforementioned user rights are a discounted price corresponding to the online service calculated based on the actual number of rights certificates that a user can obtain by consuming the online service, then the target condition specified by the user for the user rights may specifically include the lowest discounted price corresponding to the online service calculated based on the actual number of rights certificates that a user can obtain by consuming the online service; correspondingly, the aforementioned consumption demand may specifically include the consumption demand of recommending the online service with the lowest discounted price corresponding to the online service calculated based on the actual number of user rights that a user can obtain after consuming the service.

[0179] In this scenario, the aforementioned target service program, in addition to calculating the actual number of user rights a user can obtain after consuming all online services published by the service provider on the service platform, and calculating the discount price corresponding to the online service based on the actual number of rights certificates obtained by the user after consuming the online services, can further, after calculating the actual number of user rights a user can obtain after consuming all online services published by the service provider on the service platform, select the N online services with the lowest discount prices corresponding to the online service, calculated based on the actual number of user rights a user can obtain after consuming the service. Then, the selected N online services can be displayed to the user through the visual interface provided by the target service program.

[0180] In some embodiments, if the user benefit is a combination of the benefit certificate and the discount price, the target condition specified by the user for the user benefit may specifically include the highest recommendation weight value.

[0181] It should be noted that the recommendation weight value corresponding to any online service can be specifically calculated by weighting the actual number of rights certificates a user can obtain after consuming the online service with the discount price corresponding to that online service, based on that actual number. This recommendation weight value can be positively correlated with the aforementioned actual number and discount price.

[0182] In the weighted calculation of the actual quantity and the discount price, the weighting of the actual quantity and the discount price can be flexibly set according to the needs in practical applications, and will not be specifically limited in this specification.

[0183] For example, to emphasize the actual quantity in the weighting process, a higher weight can be assigned to the actual quantity; similarly, to emphasize the discount price, a higher weight can be assigned to the discount value. If the influence of the actual quantity and the discount price needs to be balanced in the weighting process, they can be assigned the same weight.

[0184] Accordingly, the aforementioned consumption demand can specifically include the demand to recommend the online service with the highest recommendation weight to the user. In this case, in addition to calculating the actual number of user rights that the user can obtain after consuming all online services published by the service provider on the service platform, and calculating the discount price corresponding to the online service based on the actual number of rights certificates that the user can obtain after consuming online services, the target service program can further perform a weighted calculation on the aforementioned actual quantity and the aforementioned discount price to obtain the recommendation weight value corresponding to all online services.

[0185] Then, from all the online services published by the service provider on the service platform, the N online services with the highest calculated recommendation weight values ​​are obtained, and these N selected online services are displayed to the user through the visual interface provided by the target service program.

[0186] In some embodiments, the basic information obtained from the service provider for calculating user rights may further include calculation rules for calculating the discount price corresponding to the online service based on the number of rights certificates that the user can obtain.

[0187] In this case, when the target service program calculates the discount price corresponding to the online service based on the actual number of rights certificates that the user can obtain by consuming the online service, it can specifically calculate the discount price corresponding to the online service based on the calculation rules in the basic information and the actual number of rights certificates that the user can obtain.

[0188] It should be noted that the specific calculation rules used to calculate the discount price corresponding to the online service based on the actual number of rights certificates that a user can obtain by consuming the aforementioned online service are not specifically limited in this specification. In practical applications, the service provider can flexibly set these rules based on specific needs.

[0189] In some embodiments, the aforementioned equity certificates may specifically include monetized equity certificates; the aforementioned calculation rules may specifically include the exchange relationship between equity certificates and preset currencies.

[0190] For example, taking the aforementioned online service as a hotel booking service, for operational purposes, the brand of the hotel booking service ultimately issues user vouchers, specifically monetary points. The calculation rules can be a points exchange rate determined by the brand based on operational needs. This exchange rate declares the exchange relationship between points and a preset currency; for example, it can be agreed that 1 RMB can be exchanged for a certain number of points. Users can then use these monetary points to offset the cost of booking a hotel.

[0191] In this case, when the aforementioned target service program further calculates the discount price corresponding to the online service based on the calculation rules and the actual number of rights certificates that the user can obtain, it can first calculate the amount of preset currency that can be exchanged for the actual number of rights certificates that the user can obtain based on the exchange relationship; then, it can further calculate the discount price corresponding to the online service based on the calculated amount of currency.

[0192] For example, taking the aforementioned online service as a hotel booking service, the discounted price is often referred to as a "rebate" in the hotel booking scenario. Brands can set a clear points exchange rate; for instance, 100 million points are approximately equivalent to 450 RMB. Assuming the brand stipulates that 1 USD earns 10 points, a user booking a hotel priced at 1000 RMB per night would earn approximately 1380 points. Therefore, the rebate price for the user booking that hotel would be 1000 - 1380 * 0.045 = 938 RMB.

[0193] It should be further noted that the service functions that the aforementioned target service program can provide to users, in addition to including calculating the user rights that users can obtain after consuming the aforementioned online services, may also be introduced into the target service program by the service provider based on specific operational needs in practical applications.

[0194] For example, taking the aforementioned online service as a hotel booking service, the target service program can also provide users with inquiry services that go down to specific stores, and when it cannot correctly answer users' inquiries based on the standard knowledge base provided by the store or brand, it can remotely initiate a call to the specific store, and so on.

[0195] In the above technical solution, by opening up the computing power of LLM deployed on the service platform to the service provider, deploying an AI service program based on LLM corresponding to the service provider on the service platform, and authorizing the service provider to grant the service program the basic information used to calculate user rights, users can use the service program to efficiently calculate the user rights they can obtain after consuming the online services published by the service provider on the service platform. This can improve the accuracy of the calculated user rights and significantly reduce the operational difficulty for users when calculating user rights.

[0196] The following describes the technical solution of this specification in detail, taking the above-mentioned online service as a hotel booking product published on the OTP platform, the above-mentioned artificial intelligence service program as an LLM-based service program called an LLM Agent, and the above-mentioned rights certificate as points.

[0197] Please see Figure 3 , Figure 3 This flowchart illustrates a method for calculating user benefits for hotel booking services, applied to a target AI service program deployed on a service platform corresponding to a hotel brand. The hotel brand publishes hotel booking services on the service platform. The target AI service program provides services to users including calculating points earned by the user after consuming the hotel booking service, comprising the following execution process:

[0198] Step 302: Obtain the hotel booking service-related demand data entered by the user in the visual interface corresponding to the artificial intelligence service program;

[0199] Step 304: Perform semantic recognition on the demand data, and determine the user's consumption demand for the hotel booking service based on the semantic recognition results; wherein, the consumption demand includes consumption demand for triggering the calculation of points that the user can obtain after consuming the hotel booking service;

[0200] Step 306: In response to the determined consumption demand of the user for the online service, based on the basic information obtained from the hotel brand for calculating the user's rights, calculate the number of points that the user can obtain after consuming services corresponding to the consumption demand for the hotel booking service.

[0201] It should be noted that steps 302-306 are a further refinement of steps 202-206 above, combined with the application scenario of points calculation for hotel booking services. For specific implementation details, please refer to the description in the previous embodiments.

[0202] The following will take the above-mentioned artificial intelligence service program as an example of an intelligent agent built on LLM, and describe in detail the implementation process of steps 302-306 with specific interaction diagrams.

[0203] Please see Figure 4 , Figure 4 This is a schematic diagram illustrating the deployment of an LLM agent on an OTP platform, as shown in this specification.

[0204] like Figure 4 As shown, a general agent corresponding to the service platform (i.e., the basic service program corresponding to the aforementioned service platform) can be deployed on the OTP platform. In addition, the computing power of the LLM deployed on the OTP platform can be opened up to specific hotel brands. A dedicated agent corresponding to the specific hotel brand (i.e., the target service program corresponding to the aforementioned service provider) can be deployed on the OTP platform. The hotel brand can authorize the dedicated agent with the basic information used to calculate points (such as points calculation rules, user membership card level, etc.), so that the dedicated agent can intelligently provide users with the service function for calculating points based on the basic information.

[0205] In this way, an ecosystem of second official websites can be created for various brands on the OTP platform, allowing each hotel brand to independently operate its dedicated agent based on its user data to provide relevant intelligent services to users.

[0206] Please continue reading Figure 4 Users can input their requirements in a visual interface provided by the client corresponding to the general agent. The client can then submit the user's input requirements to the general agent.

[0207] After obtaining the aforementioned requirement data input by the user, the general agent can perform preliminary semantic recognition on the requirement data. Based on the semantic recognition results, it can determine that the requirement data corresponds to a specific brand. Then, it can further distribute the requirement data to a dedicated agent deployed by the brand on the OTP platform, which will then continue to process the requirement data.

[0208] For example, such as Figure 4As shown, after a user enters the request data "staying at XX Hotel in Hangzhou during the May Day holiday" in the visual interface provided by the client corresponding to the general agent, the general agent performs preliminary semantic recognition and confirms that the request data corresponds to the specific hotel brand "XX Hotel". At this time, the general agent can switch the agent used by the user from the general agent to the dedicated agent deployed by "XX Hotel" on the OTP platform, and distribute the user's input request data to the dedicated agent.

[0209] Of course, in practical applications, the aforementioned dedicated agent can also be set up with an independent operation entry point; for example, the operation entry point of the aforementioned dedicated agent can be added to the hotel booking details page of the hotel brand, to the promotional activity page initiated by the hotel brand, and to the homepage of the hotel brand's online store, etc.

[0210] Please see Figure 5 , Figure 5 This is a schematic diagram illustrating a user-facing visual interface provided by a dedicated agent, as shown in this specification.

[0211] The services offered to users by this dedicated agent may include multiple functions that can trigger the calculation of points that users can earn after consuming hotel booking services.

[0212] like Figure 5 As shown, these multiple service functions may specifically include hotel recommendations, hotel cost estimates, and membership card upgrades. The dedicated agent provides a user-facing visual interface with quick access points for these service functions, allowing users to rapidly invoke them.

[0213] Among these services, hotel recommendation refers to recommending hotel products that meet the user's consumption needs (such as maximizing points earned after check-in). Hotel actuarial service refers to calculating the number of points a user can earn after consuming hotel products, as well as the corresponding rebate price. Membership card upgrade and maintenance services refer to providing users with strategies for maintaining and upgrading their membership cards.

[0214] Please see Figure 6 , Figure 6 This is a schematic diagram illustrating how a dedicated agent recommends hotels to a user.

[0215] like Figure 6As shown, in the service scenario recommended by the hotel, the dedicated agent can sample multiple rounds of conversations to interact with the user and obtain the user's input data during the interaction.

[0216] In the first round of the conversation, suppose the user enters a text command in the visual interface provided by the dedicated agent: "I want to go to Hangzhou in April. What is the most cost-effective way to book a hotel with points?"

[0217] After receiving the text command input by the user, the dedicated agent can perform semantic recognition on the text and determine the user's consumption needs based on the semantic recognition results. Then, it will make preliminary hotel recommendations for the user according to the default recommendation mode "top N hotels with the highest points return" (i.e., the default target conditions used for hotel recommendations).

[0218] The so-called "hotel with the highest points redemption" can refer to the hotel with the highest recommendation weight value. Specifically, the recommendation weight value is a weighted calculation based on the number of points a user can obtain after checking in and the hotel's redemption price calculated based on the number of points obtained.

[0219] This dedicated agent can calculate the recommendation weight of all hotel booking products published by the hotel brand on the OTP platform, and then filter out the N hotel booking products with the highest recommendation weight as the initial hotel recommendation results. Here, N is a preset threshold.

[0220] For example, in practical applications, this dedicated agent can search for hotel booking products of the brand in the vicinity of the user's location (e.g., within 5 kilometers) and then calculate the recommendation weight value of these hotel booking products.

[0221] like Figure 6 As shown, this dedicated agent, in addition to providing initial hotel recommendations, also offers users interactive options within the visual interface to manually adjust the recommendation mode. These options provide users with at least one selectable recommendation strategy. The selectable recommendation strategies offered by this dedicated agent can include the default recommendation mode "top N hotels with the highest points redemption," as well as strategies such as "top N hotels with the highest points" and "top N hotels with the lowest redemption price."

[0222] In the second round of the session, the user can interact with the available recommendation modes provided in the aforementioned visual interface to redefine the recommendation mode (i.e., the user-specified target conditions). At this point, through the interaction of two rounds of sessions, the user has successfully input their personal consumption needs into the dedicated agent, which can then re-recommend hotels based on the user's newly specified recommendation mode.

[0223] Please continue reading Figure 6 Suppose the user re-specifies the recommendation mode to "top N hotels with the highest points". The dedicated agent can calculate the actual number of points the user can obtain after consuming all hotel booking products published by the hotel brand on the OTP platform, and then filter out the N hotel booking products with the highest actual number of points to be used as further hotel recommendation results.

[0224] Of course, if the user re-specifies the recommendation mode to "top N hotels with the highest cashback", the dedicated agent can also calculate the cashback price of all hotel booking products published by the hotel brand on the OTP platform, and then filter out the N hotel booking products with the highest cashback price as further hotel recommendation results.

[0225] In the above embodiments, in the application scenario of recommending hotel booking services to users, by opening up the computing power of LLM deployed on the e-commerce platform to the hotel brand, deploying the LLM agent corresponding to the hotel brand on the service platform, and authorizing the LLM agent with basic information such as the points allocation rules for calculating points and the user's rights level with the hotel brand, the user can use the LLM agent to efficiently query the actual number of points that can be obtained after consuming services and hotel service combinations that meet the conditions specified by the user, and significantly reduce the difficulty of the user's operation when querying hotels.

[0226] Please see Figure 7 , Figure 7 This is a schematic diagram illustrating how a dedicated agent performs hotel calculations for a user-specified hotel.

[0227] like Figure 7 As shown, in the service scenario of hotel actuarial science, this dedicated agent can also interact with users through multiple rounds of sampling to obtain the user's input of demand data during the interaction process.

[0228] In the first round of the conversation, suppose the user enters a text command in the visual interface provided by the dedicated agent: "I want to calculate when is the best time to book a hotel I'm interested in to get the most points."

[0229] After receiving the text command input by the user, the dedicated agent can perform semantic recognition on the text and determine the user's consumption needs based on the semantic recognition results. Then, it can continue to ask the user a text reply such as "Okay, please tell me which hotel it is" so that the user can provide the name of the hotel for which the points need to be calculated.

[0230] In the second session, the user can enter a text command, "XXX Selected Hotels," into the visual interface provided by the dedicated agent to supplement the name of the hotel for which points need to be calculated.

[0231] After receiving the text command from the user again, the dedicated agent allows the user to successfully input their consumption needs through two rounds of interaction. The dedicated agent can then calculate the points the user can earn after staying at the hotel, calculate the hotel's rebate price based on the points earned, and then output the calculation process and results to the user through the visual interface.

[0232] Of course, in practical applications, users can also trigger the dedicated agent to calculate the highest level and lowest cashback price that the user can obtain when staying at the specified hotel by entering text commands such as "I want to calculate when the most points can be obtained by booking a hotel I like" and "I want to calculate when the most cashback price can be obtained by booking a hotel I like". The specific implementation process will not be described in detail.

[0233] In applications that accurately calculate user benefits after consuming hotel booking services on e-commerce platforms, the computing power of the LLM deployed on the e-commerce platform is opened up to hotel brands. An LLM agent corresponding to the hotel brand is deployed on the service platform, and the hotel brand authorizes the LLM agent with basic information such as the points allocation rules for calculating points and the user's benefit level with the hotel brand. This allows users to accurately calculate the points they can obtain after consuming hotel booking services on e-commerce platforms, significantly reducing the operational difficulty for users when calculating points.

[0234] Please see Figure 8 , Figure 8 This is a schematic diagram illustrating a strategy for a dedicated agent to maintain a user's membership card level, as shown in this specification.

[0235] like Figure 8As shown, in the service scenario of developing membership card retention strategies for users, the dedicated agent can also interact with users through multiple rounds of conversations to obtain the user's input data during the interaction process.

[0236] In the first round of the conversation, suppose the user enters a text command for "retention recommendation" in the visual interface provided to the user by the dedicated agent.

[0237] After receiving the text command input by the user, the dedicated agent can perform semantic recognition on the text and determine the user's consumption needs based on the semantic recognition results. Then, it will continue to ask the user a text reply asking, "How would you like to maintain your status?" and provide the user with selectable status maintenance strategies, which the user can then add.

[0238] For example, Figure 8 The available retention strategies shown can include strategies such as "hotel with the highest points", "hotel with the lowest point rebate", and "hotel with the highest point rebate".

[0239] In the second round of the session, users can interact with the available retention strategies provided in the aforementioned visual interface to specify their desired retention strategy (i.e., the user-defined target conditions). Through these two rounds of interaction, the user successfully inputs their personal consumption needs into the dedicated agent. Based on the user's specified retention strategy, the agent can then filter hotel booking combinations that match that strategy and generate a consumption strategy tailored to that combination.

[0240] For example, please continue to see Figure 7 Assuming the user's specified retention strategy is "the hotel with the highest points", the dedicated agent can calculate the number of points the user can obtain after consuming all hotel booking products published by the hotel brand on the OTP platform. Then, based on the user's specified retention strategy, the agent can filter the combination of hotel booking products with the highest points after the stay and generate a consumption strategy for the user for that combination.

[0241] Of course, if the user's specified retention strategy is "hotel with the lowest cashback price," then the dedicated agent can calculate the cashback price for all hotel booking products offered by that hotel brand on the OTP platform. Based on the user's retention strategy, it can then filter for the combination of hotel booking products with the lowest cashback price and generate a consumption strategy for that combination. Similarly, if the user's specified retention strategy is "hotel with the highest points cashback," this "hotel with the highest points cashback" can refer to the hotel with the highest recommendation weight value. This recommendation weight value is specifically a weighted calculation based on the number of points the user can earn after check-in and the cashback price of the hotel calculated based on that number of points. Further details are omitted here.

[0242] At this point, the dedicated agent can calculate the recommendation weight of all hotel booking products published by the hotel brand on the OTP platform, and then, based on the user's specified level retention strategy, select the combination of hotel booking products with the highest recommendation weight for the user, and generate a consumption strategy for the user based on that combination.

[0243] Please see Figure 9 , Figure 9 This is a schematic diagram illustrating a membership card upgrade strategy developed by a dedicated agent for a user, as shown in this specification.

[0244] like Figure 9 As shown, in the service scenario of developing membership card upgrade strategies for users, the dedicated agent can also sample multiple rounds of conversations to interact with users and obtain the user's input data during the interaction process.

[0245] In the first round of the conversation, suppose the user enters a text command for "fast upgrade recommendation" in the visual interface provided by the dedicated agent.

[0246] After receiving the text command input by the user, the dedicated agent can perform semantic recognition on the text and determine the user's consumption needs based on the semantic recognition results. Then, it will continue to ask the user questions by replying with a text message such as "How would you like to upgrade quickly?" and provide the user with selectable retention strategies, which the user can then supplement with the desired retention strategy.

[0247] For example, Figure 9 The upgrade strategies shown can still include upgrade strategies such as "hotel with the highest points", "hotel with the lowest cashback price", and "hotel with the highest points cashback".

[0248] In the second round of the session, users can interact with the available upgrade strategies provided in the aforementioned visual interface to specify their desired upgrade strategy (i.e., the user-defined target condition). Through these two rounds of interaction, the user successfully inputs their personal consumption needs into the dedicated agent. Based on the user-specified upgrade strategy, the agent can then filter hotel booking combinations that match that strategy and generate a consumption strategy tailored to that combination.

[0249] For example, please continue to see Figure 9 Assuming the user's upgrade strategy is "the hotel with the highest points", the dedicated agent can calculate the number of points the user can earn after consuming all hotel booking products offered by the hotel brand on the OTP platform. Then, based on the user's upgrade strategy, the agent can filter the combination of hotel booking products that will earn the highest points after the stay and generate a consumption strategy for the user based on that combination.

[0250] In application scenarios involving maintaining or upgrading a user's privilege level with a hotel brand, the computing power of the LLM deployed on the e-commerce platform is opened to the hotel brand. An LLM agent corresponding to the hotel brand is deployed on the service platform. The hotel brand authorizes the LLM agent with the points allocation rules used to calculate points and basic information such as the user's privilege level with the hotel brand. This allows the user to efficiently query the actual number of points that can be obtained after consuming services, ensuring that the user's privilege level does not decrease or increases, and meeting the hotel service combination conditions specified by the user. This significantly reduces the difficulty for users to maintain or upgrade their privilege level.

[0251] Corresponding to the embodiments of the foregoing methods, this specification also provides embodiments of apparatus, electronic devices, and storage media.

[0252] Figure 10 This is a schematic structural diagram of an electronic device provided in an exemplary embodiment. Please refer to... Figure 10At the hardware level, the device includes a processor 1002, an internal bus 1004, a network interface 1006, memory 1008, and non-volatile memory 1010, and may also include other necessary hardware. One or more embodiments of this specification can be implemented in software, for example, the processor 1002 reads the corresponding computer program from the non-volatile memory 1010 into memory 908 and then runs it. Of course, besides software implementation, one or more embodiments of this specification do not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. That is to say, the execution entity of the following processing flow is not limited to individual logic units, but can also be hardware or logic devices.

[0253] like Figure 11 As shown, Figure 11 This is a block diagram illustrating a user rights calculation device according to an exemplary embodiment, which can be applied to, for example... Figure 10 The illustrated electronic device is used to implement the technical solution of this specification. The device can be applied to a target artificial intelligence service program deployed on a service platform, corresponding to a service provider; wherein the target artificial intelligence service program is a service program built based on LLM; the service provider publishes online services on the service platform; the service functions provided by the target service program to users include calculating the user rights that the user can obtain after consuming the online service; the device 100 includes:

[0254] The first acquisition module 1101 acquires the user's input requirement data;

[0255] The first determining module 1102 performs semantic recognition on the demand data based on the LLM, and determines the user's consumption demand for the online service based on the semantic recognition result; wherein, the consumption demand includes consumption demand for triggering the calculation of user rights that the user can obtain after consuming the online service;

[0256] The first calculation module 1103, in response to the determined consumption demand of the user for the online service, calculates the number of points that the user can obtain after consuming services corresponding to the consumption demand for the hotel booking service based on the basic information obtained from the hotel brand for calculating the user's rights.

[0257] like Figure 12 As shown, Figure 12 This is a block diagram illustrating an apparatus for calculating user rights for hotel booking services according to an exemplary embodiment. This apparatus can also be applied to, for example... Figure 10The illustrated electronic device is used to implement the technical solution of this specification. The device can be applied to a target artificial intelligence service program deployed on a service platform corresponding to a hotel brand; wherein the hotel brand publishes a hotel booking service on the service platform; the service functions provided to users by the target artificial intelligence service program include calculating the points that the user can obtain after consuming the hotel booking service; the device 120 includes:

[0258] The second acquisition module 1201 acquires the demand data related to the hotel booking service input by the user in the visual interface corresponding to the LLM agent;

[0259] The second determining module 1202 performs semantic recognition on the demand data and determines the user's consumption demand for the hotel booking service based on the semantic recognition result; wherein, the consumption demand includes consumption demand for triggering the calculation of points that the user can obtain after consuming the hotel booking service.

[0260] The second calculation module 1203, in response to the determined consumption demand of the user for the hotel booking service, calculates the user rights that the user can obtain after consuming services corresponding to the consumption demand in the online service based on the basic information obtained from the service provider for calculating the user rights.

[0261] Accordingly, this specification also provides an electronic device including a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement all the steps in the previously described method flow.

[0262] Accordingly, this specification also provides a computer-readable storage medium having stored thereon executable computer program instructions; wherein, when executed by a processor, the instructions implement all the steps in the previously described method flow.

[0263] Accordingly, this specification also provides a computer program product having executable computer program instructions stored thereon; wherein, when the computer program instructions are executed by a processor, they implement all the steps in the previously described method flow.

[0264] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. A typical implementation device is a server system. Of course, it is not excluded that with the future development of computer technology, the computer implementing the functions of the above embodiments may be, for example, a personal computer, a laptop computer, an in-vehicle human-machine interaction device, 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 any combination of these devices.

[0265] While one or more embodiments of this specification provide the operational steps of the methods described in the embodiments or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or end product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, it is not excluded that the process, method, product, or apparatus that includes the elements may also have other identical or equivalent elements. For example, the use of terms such as "first," "second," etc., is used to indicate names and does not indicate any particular order.

[0266] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, when implementing one or more of these specifications, the functions of each module can be implemented in one or more software and / or hardware components, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0267] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0268] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0269] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0270] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0271] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0272] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. 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 memory (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, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage, graphene storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0273] Those skilled in the art will understand that one or more embodiments of this specification can be provided as a method, system, or computer program product. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. 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, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0274] One or more embodiments of this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. One or more embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In a distributed computing environment, program modules can reside in local and remote computer storage media, including storage devices.

[0275] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, system embodiments are basically similar to method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. In the description of this specification, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this specification. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0276] The above description is merely an embodiment of one or more embodiments of this specification and is not intended to limit the scope of this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims.

Claims

1. A method for calculating user rights for hotel booking services, applied to a target AI service program deployed on a service platform corresponding to a hotel brand; wherein, The target AI service program is a service program built on LLM; the hotel brand has published a hotel booking service on the service platform. The target AI service program provides users with the following service functions: calculating the points a user can earn after consuming the hotel booking service; the method includes: Obtain the hotel booking service-related demand data entered by the user in the visual interface corresponding to the target artificial intelligence service program; The demand data is semantically recognized, and the user's consumption demand for the hotel booking service is determined based on the semantic recognition results; wherein, the consumption demand includes the consumption demand used to trigger the calculation of points that the user can obtain after consuming the hotel booking service. In response to the determined consumption demand of the user for the hotel booking service, based on the basic information obtained from the hotel brand for calculating the user's rights, the number of points that the user can obtain after consuming services corresponding to the consumption demand for the hotel booking service is calculated.

2. The method as described in claim 1, wherein the basic information includes: The points allocation rules corresponding to the hotel brand; and the user's benefit level for the hotel booking service, for which the hotel brand has authorized data. Based on the aforementioned basic information, the calculation of the number of points a user can earn after consuming services corresponding to their consumption needs in the hotel booking service includes: The number of points allocated to a user's rights level is determined based on the user rights rules. Using the allocated points as the base allocation, the actual number of points a user can earn after consuming the hotel booking service is further calculated.

3. The method as described in claim 1, wherein the service platform further deploys a basic artificial intelligence service program based on LLM corresponding to the service platform; Obtain user input request data, including: The system obtains user-inputted demand data distributed by the basic artificial intelligence service program corresponding to the service platform; wherein, the demand data is initially semantically recognized by the basic artificial intelligence service, and after determining that the demand data corresponds to the hotel brand based on the semantic recognition result, it is distributed to the target artificial intelligence service program.

4. The method as described in claim 3, further calculating the actual number of points a user can obtain after consuming the hotel booking service, using the allocated points quantity as the base allocation quantity, includes: Obtain operational information for the hotel booking service provided by the merchant corresponding to the hotel booking service; wherein, the operational information includes the additional number of points that a user can obtain after consuming the hotel booking service; The points allocation quantity is used as the base allocation quantity, and added to the additional quantity to obtain the actual number of points that the user can obtain after consuming services corresponding to the consumption needs for the hotel booking service.

5. The method as described in claim 4, wherein the consumer demand includes the consumer demand for recommending hotel booking services to users; Before using the allocated points as the base allocation and further calculating the actual number of points a user can earn after consuming services related to the hotel booking service, the process also includes: The system outputs at least one recommendation strategy to the user through a visual interface corresponding to the target service program; wherein the recommendation strategy indicates the conditions that the actual number of points the user can obtain after consuming the service must meet. Obtain the target recommendation strategy selected by the user from the at least one recommendation strategy; Using the allocated points as the base allocation, the actual number of points a user can earn after consuming services related to the hotel booking service is further calculated, including: In response to the target recommendation strategy selected by the user from the at least one recommendation strategy, the number of points allocated is used as the base allocation number to further calculate the actual number of points that the user can obtain after consuming services for all hotel booking services released by the hotel brand. In response to the calculated actual number of points a user can earn after consuming services for all the hotel booking services, N hotel booking services are further selected from all the hotel booking services whose actual number of points a user can earn after consuming services satisfies the conditions indicated by the target recommendation strategy; wherein, N is a preset threshold. The N hotel booking services are displayed to the user through the visual interface.

6. The method of claim 5, wherein the consumption demand includes the consumption demand for calculating the actual number of points a user can obtain after consuming services for a specified target hotel booking service; Before using the allocated points as the base allocation and further calculating the actual number of points a user can earn after consuming services related to the hotel booking service, the process also includes: The system interacts with the user through a visual interface corresponding to the target service program to obtain the user's input of the specified target hotel booking service. Using the allocated points as the base allocation, the actual number of points a user can earn after consuming services related to the hotel booking service is further calculated, including: In response to the obtained target hotel booking service, the points allocation quantity is used as the base allocation quantity to further calculate the actual number of points that the user can obtain after consuming the service for the target hotel booking service; The actual number of points a user can earn after consuming the service for the target hotel booking will be displayed to the user through the visualization interface.

7. The method of claim 6, wherein the consumption demand includes a consumption request for a hotel booking service package that recommends to the user the actual number of points earned after consuming the service, and that ensures the user's benefit level does not decrease. Before using the allocated points as the base allocation and further calculating the actual number of points a user can earn after consuming services related to the hotel booking service, the process also includes: The system outputs at least one recommendation strategy to the user through a visual interface corresponding to the target service program; wherein the recommendation strategy indicates the conditions that the user can meet for the actual number of points that can be obtained after consuming the hotel booking service in the hotel booking service package. Obtain the target recommendation strategy selected by the user from the at least one recommendation strategy; Using the allocated points as the base allocation, the actual number of points a user can earn after consuming services related to the hotel booking service is further calculated, including: In response to the target recommendation strategy selected by the user from the at least one recommendation strategy, the number of points allocated is used as the base allocation number to further calculate the actual number of points that the user can obtain after consuming services for all hotel booking services released by the hotel brand. In response to the calculated actual number of points a user could earn after consuming services for all the hotel booking services, the system further filters hotel booking service combinations for the user from all the hotel booking services and generates a consumption strategy for the user for the hotel booking service combinations; wherein, the consumption strategy is a consumption strategy that ensures the user's benefit level does not decline based on the actual number of points earned by the user after consuming services for the hotel booking services in the hotel booking service combinations; and the earned points satisfy the conditions indicated by the target level preservation strategy. The hotel booking service package and the consumption strategy are displayed to the user through the visual interface.

8. The method of claim 7, wherein the consumption demand includes a consumption request for a hotel booking service package that recommends to the user the actual number of points earned after consuming the service, which can ensure an increase in the user's benefit level; Before using the allocated points as the base allocation and further calculating the actual number of points a user can earn after consuming services related to the hotel booking service, the process also includes: The system outputs at least one recommendation strategy to the user through a visual interface corresponding to the target service program; wherein the recommendation strategy indicates the conditions that the user can meet for the actual number of points that can be obtained after consuming the hotel booking service in the hotel booking service package. Obtain the target recommendation strategy selected by the user from the at least one recommendation strategy; Using the allocated points as the base allocation, the actual number of points a user can earn after consuming services related to the hotel booking service is further calculated, including: In response to the target recommendation strategy selected by the user from the at least one recommendation strategy, the number of points allocated is used as the base allocation number to further calculate the actual number of points that the user can obtain after consuming services for all hotel booking services released by the hotel brand. In response to the calculated actual number of points a user could earn after consuming services for all the hotel booking services, the system further filters hotel booking service combinations for the user from all the hotel booking services and generates a consumption strategy for the user for the hotel booking service combinations; wherein, the consumption strategy is a consumption strategy that ensures that the actual number of points the user earns after consuming services for hotel booking services in the hotel booking service combinations can ensure that the user's benefit level increases; and, the points earned meet the conditions indicated by the target level maintenance strategy. The hotel booking service package and the consumption strategy are displayed to the user through the visual interface.

9. The method of claim 8, wherein the at least one recommendation strategy comprises any or a combination of the following: The user can actually obtain the maximum number of points; The lowest discounted price corresponding to the hotel booking service is calculated based on the actual number of points that the user can obtain. The recommendation has the highest weight; among them, The highest recommended weight value is a weighted value obtained by weighting the actual number of points a user can obtain and the discount price calculated based on the actual number of points a user can obtain; the recommended weight value is positively correlated with the actual number of points and the discount price.

10. The method of claim 9, wherein the points include monetized points; Calculating the discounted price corresponding to the hotel booking service includes: Based on the exchange relationship between the monetized points and the designated currency, calculate the amount of the designated currency that the user can exchange for the actual number of points they can obtain. Based on the calculated amount of the specified currency, a discount price corresponding to the hotel booking service is further calculated.

11. The method of claim 10, wherein the artificial intelligence service program includes an agent built on an LLM.

12. A method for calculating user rights, applied to a target artificial intelligence service program deployed on a service platform that corresponds to a service provider; wherein, The target artificial intelligence service program is a service program built on LLM; the service provider publishes online services on the service platform; The target service program provides users with the following service functions: calculating the user rights that the user can obtain after consuming the online service; the method includes: Obtain user input data; The demand data is semantically identified, and the user's consumption demand for the online service is determined based on the semantic identification results; wherein, the consumption demand includes the consumption demand used to trigger the calculation of user rights that the user can obtain after consuming the online service; In response to the determined consumption demand of the user for the online service, based on the basic information obtained from the service provider for calculating the user's rights, the user rights that the user can obtain after consuming services corresponding to the consumption demand for the online service are calculated.

13. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 12.

14. A computer program product comprising a computer program that, when executed by a processor, implements the steps of the method of any one of claims 1 to 12.

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