Customized product service method and system fusing user preferences

Abstract

The invention discloses a customized product service method and system fusing user preferences, and relates to the technical field of data processing, and the method comprises the steps: obtaining all services of a product selected by a user, and setting all services as a service set; performing feasibility analysis on all services in the service set according to a preset feasibility analysis algorithm, removing infeasible services, and updating the service set; obtaining user preference information according to the user historical data, and performing perceptual value scoring on services in the service set through a preset perceptual value model; and sorting the services in the service set according to the descending order of the perception value scores, and pushing the services to the user according to the sequence. Through comprehensive analysis of the user behavior data, the interest and demand changes of the user are accurately identified, customized products and services are provided based on the user preference information, and the matching degree of the services and the satisfaction degree of the user are improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a customized product service method and system integrating user preferences. Background Art

[0002] Customized product services refer to providing personalized products or services based on the specific needs and preferences of users. This service model emphasizes the personalized needs of users, and tailors the most suitable products or services for users by collecting and analyzing relevant information of users. In the prior art, there are many methods for product customization services on the market, which usually provide corresponding products or services based on the basic needs of users. However, there are some shortcomings in the prior art: Lack of in-depth analysis of user preferences: Most customized service methods are based only on the basic information of users and simple demand analysis, and cannot accurately capture the real preferences and demand changes of users; Service updates are not timely: Due to the lack of an effective user feedback mechanism, existing customized services are difficult to update and adjust service content in a timely manner, and cannot meet the changing needs of users; The accuracy of recommended services is insufficient: The recommendation algorithms in the prior art usually lack targeted analysis, resulting in a large gap between the recommended services or products and the actual needs of users. Summary of the invention

[0003] Based on the above-mentioned shortcomings of the prior art, the purpose of the present invention is to provide a customized product service method and system integrating user preferences to solve the above-mentioned technical problems.

[0004] To achieve the above object, the present invention provides the following technical solution: a customized product service method integrating user preferences, comprising:

[0005] Get all services of the product selected by the user and set all services as service collection;

[0006] Perform feasibility analysis on all services in the service set according to the preset feasibility analysis algorithm, remove infeasible services, and update the service set;

[0007] Obtain user preference information based on user historical data, and use a preset perceived value model to rate the perceived value of services in the service set;

[0008] Sort the services in the service set in descending order of perceived value scores, and push the services to users in that order.

[0009] The present invention is further configured to perform feasibility analysis on all services in the service set according to a preset feasibility analysis algorithm, including:

[0010] Perform technical feasibility analysis on all services in the service set according to a preset technical feasibility analysis algorithm;

[0011] Perform economic feasibility analysis on all services in the service set according to a preset economic feasibility analysis algorithm;

[0012] Perform time feasibility analysis on all services in the service set according to a preset time feasibility analysis algorithm;

[0013] When the results of the technical feasibility analysis, the economic feasibility analysis and the time feasibility analysis are all feasible, the result of the feasibility analysis of the service is feasible; when any result of the technical feasibility analysis, the economic feasibility analysis and the time feasibility analysis is infeasible, the result of the feasibility analysis of the service is infeasible.

[0014] The present invention is further configured to perform a technical feasibility analysis on all services in the service set according to a preset technical feasibility analysis algorithm, including:

[0015] Perform resource availability analysis, technical complexity analysis, and maintenance difficulty analysis on all services in the service set to obtain resource availability analysis evaluation scores, technical complexity analysis evaluation scores, and maintenance difficulty analysis evaluation scores;

[0016] The technical feasibility analysis evaluation score is calculated according to the resource availability analysis evaluation score, the technical complexity analysis evaluation score and the maintenance difficulty analysis evaluation score, wherein the calculation logic of the technical feasibility analysis evaluation score is: Te score is the technical feasibility analysis and evaluation score, Re is the resource availability analysis and evaluation score, Co is the technical complexity analysis and evaluation score, and Ma is the maintenance difficulty analysis and evaluation score;

[0017] When the technical feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the technical feasibility analysis is feasible; when the technical feasibility analysis evaluation score is less than the preset threshold, the result of the technical feasibility analysis is infeasible.

[0018] The present invention is further configured to perform economic feasibility analysis on all services in the service set according to a preset economic feasibility analysis algorithm, including:

[0019] Performing expected benefit analysis, implementation cost analysis, and fund availability analysis on all services in the service set to obtain an expected benefit analysis evaluation score, an implementation cost analysis evaluation score, and a fund availability analysis evaluation score;

[0020] The economic feasibility analysis evaluation score is calculated according to the expected benefit analysis evaluation score, the implementation cost analysis evaluation score and the capital availability analysis evaluation score, wherein the calculation logic of the economic feasibility analysis evaluation score is: E score is the economic feasibility analysis evaluation score, Be is the expected benefit analysis evaluation score, Ct is the implementation cost analysis evaluation score, and Af is the capital availability analysis evaluation score;

[0021] When the economic feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the economic feasibility analysis is feasible; when the economic feasibility analysis evaluation score is less than the preset threshold, the result of the economic feasibility analysis is infeasible.

[0022] The present invention is further configured to perform time feasibility analysis on all services in the service set according to a preset time feasibility analysis algorithm, including:

[0023] Perform development time analysis, time resource availability analysis, and time resource adaptability analysis on all services in the service set to obtain development time analysis evaluation scores, time resource availability analysis evaluation scores, and time resource adaptability analysis evaluation scores;

[0024] The time feasibility analysis evaluation score is calculated according to the development time analysis evaluation score, the time resource availability analysis evaluation score and the time resource adaptability analysis evaluation score, wherein the calculation logic of the economic feasibility analysis evaluation score is: Ti score is the time feasibility analysis and evaluation score, Du is the development time analysis and evaluation score, Ta is the time resource availability analysis and evaluation score, and Ar is the time resource fit analysis and evaluation score;

[0025] When the time feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the time feasibility analysis is feasible; when the time feasibility analysis evaluation score is less than the preset threshold, the result of the time feasibility analysis is infeasible.

[0026] The present invention is further configured to obtain user preference information based on user historical data, and to score the perceived value of services in the service set through a preset perceived value model, including:

[0027] Obtain the number of times a service is used in the user's historical data, sort the services in descending order according to the number of times the services are used, and obtain a preset number of services and feature vectors of the services;

[0028] The service feature vector is weighted according to the number of times the service is used, and the user preference vector is calculated;

[0029] The similarity between the user preference vector and the feature vectors of the services in the service set is calculated to obtain a perceived value score, wherein the similarity of the feature vectors is calculated using the cosine similarity of the vectors.

[0030] The present invention is further configured such that the construction logic of the feature vector of the service includes:

[0031] Obtain the service category and functional characteristics of the service, and use One-Hot encoding to convert the service category and functional characteristics into a numerical vector;

[0032] The service category and the numerical vector of the functional characteristics are linked to obtain the characteristic vector of the service.

[0033] The present invention is further configured to weight the service feature vector according to the number of times the service is used, and calculate the user preference vector, and the calculation logic is: U p is the user preference vector, n is the preset number, N i is the number of times the i-th service is used, N is the sum of the number of times the first n services are used, V i is the feature vector of the ith service.

[0034] The present invention also provides a customized product service system integrating user preferences, the system comprising:

[0035] Acquisition module: obtains all services of the product selected by the user and sets all services as a service collection;

[0036] Analysis module: Perform feasibility analysis on all services in the service set according to the preset feasibility analysis algorithm, remove infeasible services, and update the service set;

[0037] Scoring module: obtains user preference information based on user historical data, and uses a preset perceived value model to score the perceived value of services in the service set;

[0038] Sorting module: Sort the services in the service set in descending order according to the perceived value score, and push the services to the user in order.

[0039] The present invention provides a customized product service method and system integrating user preferences. The method obtains all services of a product selected by a user and sets all services as a service set; performs feasibility analysis on all services in the service set according to a preset feasibility analysis algorithm, removes infeasible services, and updates the service set; obtains user preference information according to user historical data, and performs perceived value scoring on services in the service set according to a preset perceived value model; sorts the services in the service set in descending order of perceived value scores, and pushes the services to the user in order, and the beneficial effects produced include:

[0040] 1. The present invention can accurately identify changes in user interests and needs through comprehensive analysis of user behavior data, and provide tailored products and services based on user preference information, thereby improving service matching and user satisfaction;

[0041] 2. The present invention comprehensively evaluates the recommendation results by combining multiple factors such as technology, economy and time to ensure practical operability. Through comprehensive evaluation and real-time optimization, it effectively reduces the risks in the implementation of customized services and improves the success rate and reliability of the services.

[0042] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0044] Figure 1 A flowchart of a customized product service method integrating user preferences is shown as an exemplary embodiment of the present invention;

[0045] Figure 2 The structure diagram of a customized product service system integrating user preferences is shown as an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will describe the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention, not for limiting the scope of protection of the present invention.

[0047] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0048] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0049] Embodiment 1

[0050] A customized product service method that incorporates user preferences, such as Figure 1 As shown, including:

[0051] Get all services of the product selected by the user and set all services as service collection;

[0052] Perform feasibility analysis on all services in the service set according to the preset feasibility analysis algorithm, remove infeasible services, and update the service set;

[0053] Obtain user preference information based on user historical data, and use a preset perceived value model to rate the perceived value of services in the service set;

[0054] Sort the services in the service set in descending order of perceived value scores, and push the services to users in that order.

[0055] Specifically, customized product services refer to providing personalized products or services based on the specific needs and preferences of users. This service model emphasizes the personalized needs of users and collects and analyzes relevant information of users to tailor the most suitable products or services for users. For the product selected by the user, all its associated services are obtained. The implementation process of associated services includes demand analysis, system design, module development, interface integration, testing and deployment.

[0056] The present invention is further configured to perform feasibility analysis on all services in the service set according to a preset feasibility analysis algorithm, including:

[0057] Performing a technical feasibility analysis on all services in the service set according to a preset technical feasibility analysis algorithm; the present invention is further configured to perform a technical feasibility analysis on all services in the service set according to a preset technical feasibility analysis algorithm, including:

[0058] Perform resource availability analysis, technical complexity analysis and maintenance difficulty analysis on all services in the service set to obtain resource availability analysis evaluation scores, technical complexity analysis evaluation scores and maintenance difficulty analysis evaluation scores; specifically, resource availability analysis is used to evaluate whether the resources required to implement the service are sufficient and available, and a resource availability analysis evaluation score is generated through manual review, with a value of 0-10; technical complexity analysis is used to evaluate the technical difficulty and complexity of implementing the service, and a technical complexity analysis evaluation score is generated through manual review, with a value of 0-10; maintenance difficulty analysis is used to evaluate the difficulty of maintenance and support of the service after deployment, and a maintenance difficulty analysis evaluation score is generated through manual review, with a value of 0-10.

[0059] The technical feasibility analysis evaluation score is calculated according to the resource availability analysis evaluation score, the technical complexity analysis evaluation score and the maintenance difficulty analysis evaluation score, wherein the calculation logic of the technical feasibility analysis evaluation score is: Te score is the technical feasibility analysis and evaluation score, Re is the resource availability analysis and evaluation score, Co is the technical complexity analysis and evaluation score, and Ma is the maintenance difficulty analysis and evaluation score. The above calculation logic provides a comprehensive technical feasibility score to help decision makers fully understand the technical feasibility of each service.

[0060] When the technical feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the technical feasibility analysis is feasible; when the technical feasibility analysis evaluation score is less than the preset threshold, the result of the technical feasibility analysis is infeasible.

[0061] The present invention is further configured to perform economic feasibility analysis on all services in the service set according to a preset economic feasibility analysis algorithm, including:

[0062] Perform expected benefit analysis, implementation cost analysis and fund availability analysis on all services in the service set to obtain expected benefit analysis evaluation scores, implementation cost analysis evaluation scores and fund availability analysis evaluation scores; specifically, expected benefit analysis is used to evaluate the expected economic benefits of the service after implementation; implementation cost analysis is used to evaluate the total cost required for the implementation of the service; fund availability analysis is used to evaluate the availability of funds required for the project. The expected benefit analysis evaluation scores, implementation cost analysis evaluation scores and fund availability analysis evaluation scores are generated through manual review and have values ​​of 0-10.

[0063] The economic feasibility analysis evaluation score is calculated according to the expected benefit analysis evaluation score, the implementation cost analysis evaluation score and the capital availability analysis evaluation score, wherein the calculation logic of the economic feasibility analysis evaluation score is: E score is the economic feasibility analysis evaluation score, Be is the expected benefit analysis evaluation score, Ct is the implementation cost analysis evaluation score, and Af is the fund availability analysis evaluation score. The above calculation logic provides a comprehensive economic feasibility score to help decision makers fully understand the economic feasibility of each service;

[0064] When the economic feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the economic feasibility analysis is feasible; when the economic feasibility analysis evaluation score is less than the preset threshold, the result of the economic feasibility analysis is infeasible.

[0065] Performing a time feasibility analysis on all services in a service set according to a preset time feasibility analysis algorithm; the present invention is further configured to perform a time feasibility analysis on all services in a service set according to a preset time feasibility analysis algorithm, including:

[0066] Development time analysis, time resource availability analysis and time resource adaptability analysis are performed on all services in the service set to obtain evaluation scores for development time analysis, time resource availability analysis and time resource adaptability analysis. Specifically, development time analysis is used to evaluate the time required to complete each service; time resource availability analysis is used to evaluate the time resources available during the project; time resource adaptability analysis is used to evaluate the degree of match between project time resources and the time required for development. The development time analysis evaluation score, time resource availability analysis evaluation score and time resource adaptability analysis evaluation score are generated through manual review, with values ​​ranging from 0 to 10.

[0067] The time feasibility analysis evaluation score is calculated according to the development time analysis evaluation score, the time resource availability analysis evaluation score and the time resource adaptability analysis evaluation score, wherein the calculation logic of the economic feasibility analysis evaluation score is: Ti score is the time feasibility analysis and evaluation score, Du is the development requirement time analysis and evaluation score, Ta is the time resource availability analysis and evaluation score, and Ar is the time resource fit analysis and evaluation score. The above calculation logic provides a comprehensive time feasibility score to help decision makers fully understand the time feasibility of each service.

[0068] When the time feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the time feasibility analysis is feasible; when the time feasibility analysis evaluation score is less than the preset threshold, the result of the time feasibility analysis is infeasible.

[0069] When the results of the technical feasibility analysis, the economic feasibility analysis and the time feasibility analysis are all feasible, the result of the feasibility analysis of the service is feasible; when any result of the technical feasibility analysis, the economic feasibility analysis and the time feasibility analysis is infeasible, the result of the feasibility analysis of the service is infeasible.

[0070] The present invention is further configured to obtain user preference information based on user historical data, and to score the perceived value of services in the service set through a preset perceived value model, including:

[0071] The number of times a service is used in the user's historical data is obtained, and the services are sorted in descending order according to the number of times the services are used, and a preset number of services and feature vectors of the services are obtained; specifically, the number of times all services used by the user are counted, and service usage records are extracted from the user's historical behavior data. According to the number of times the services are used in the user's historical data, the services are sorted in descending order according to the number of times they are used, and the service that the user uses the most times is determined by the number of times the service is used, so as to provide a basis for subsequent feature extraction and preference vector calculation; the present invention is further configured that the construction logic of the feature vector of the service includes:

[0072] The service category and functional features of the service are obtained, and the service category and functional features are converted into numerical vectors using One-Hot coding. Specifically, One-Hot coding is a feature coding method, which is mainly used to convert categorical data into a numerical form suitable for processing by machine learning algorithms, and each category is represented as a binary vector, in which only one element is 1 and the other elements are 0. In a feasible embodiment of the present invention, for three categories, including entertainment, education and health, they can be represented as: Entertainment: [1,0,0] Education: [0,1,0] Health: [0,0,1]. There is no restriction on the categories here, and the functional features are also converted according to the above logic. The service features are standardized through One-Hot coding to ensure the consistency of the feature vector, provide rich service feature information, and provide a basis for preference vector calculation and similarity calculation.

[0073] The service category and the numerical vector of the functional characteristics are linked to obtain the characteristic vector of the service.

[0074] The characteristic vector of the service is weighted according to the number of times the service is used, and the user preference vector is calculated. The present invention is further configured to weight the characteristic vector of the service according to the number of times the service is used, and the user preference vector is calculated. The calculation logic is: U p is the user preference vector, n is the preset number, N i is the number of times the i-th service is used, N is the sum of the number of times the first n services are used, V i is the feature vector of the ith service. By calculating the user preference vector, the user’s preference for each service feature is clarified.

[0075] The similarity between the user preference vector and the feature vector of the service in the service set is calculated to obtain the perceived value score. The similarity of the feature vector is calculated by the cosine similarity of the vector. By calculating the similarity, the user preference and service characteristics are accurately matched.

[0076] Embodiment 2

[0077] See also Figure 2 , the exemplary customized product service system integrating user preferences includes:

[0078] Acquisition module: obtains all services of the product selected by the user and sets all services as a service collection;

[0079] Analysis module: Perform feasibility analysis on all services in the service set according to the preset feasibility analysis algorithm, remove infeasible services, and update the service set;

[0080] Scoring module: obtains user preference information based on user historical data, and uses a preset perceived value model to score the perceived value of services in the service set;

[0081] Sorting module: Sort the services in the service set in descending order according to the perceived value score, and push the services to the user in order.

[0082] It should be noted that the customized product service system integrating user preferences provided in the above embodiment and the customized product service method integrating user preferences provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs operations has been described in detail in the method embodiment and will not be repeated here. In actual applications, the customized product service system integrating user preferences provided in the above embodiment can distribute the above functions to different functional modules as needed, that is, divide the internal structure of the system into different functional modules to complete all or part of the functions described above, and this is not limited here.

[0083] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0084] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0085] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0086] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0087] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0088] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0089] In the several embodiments provided in the present application, it should be understood that the disclosed system can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0090] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0091] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0092] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0093] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A customized product service method integrating user preferences, characterized in that: include: Get all services of the product selected by the user and set all services as service collection; Perform feasibility analysis on all services in the service set according to the preset feasibility analysis algorithm, remove infeasible services, and update the service set; Obtain user preference information based on user historical data, and use a preset perceived value model to rate the perceived value of services in the service set; Sort the services in the service set in descending order of perceived value scores, and push the services to users in that order.

2. A customized product service method integrating user preferences according to claim 1, characterized in that: Perform feasibility analysis on all services in the service set according to the preset feasibility analysis algorithm, including: Perform technical feasibility analysis on all services in the service set according to a preset technical feasibility analysis algorithm; Perform economic feasibility analysis on all services in the service set according to a preset economic feasibility analysis algorithm; Perform time feasibility analysis on all services in the service set according to a preset time feasibility analysis algorithm; When the results of the technical feasibility analysis, the economic feasibility analysis and the time feasibility analysis are all feasible, the result of the feasibility analysis of the service is feasible; when any result of the technical feasibility analysis, the economic feasibility analysis and the time feasibility analysis is infeasible, the result of the feasibility analysis of the service is infeasible.

3. A customized product service method integrating user preferences according to claim 2, characterized in that: Perform technical feasibility analysis on all services in the service set according to the preset technical feasibility analysis algorithm, including: Perform resource availability analysis, technical complexity analysis, and maintenance difficulty analysis on all services in the service set to obtain resource availability analysis evaluation scores, technical complexity analysis evaluation scores, and maintenance difficulty analysis evaluation scores; The technical feasibility analysis evaluation score is calculated according to the resource availability analysis evaluation score, the technical complexity analysis evaluation score and the maintenance difficulty analysis evaluation score, wherein the calculation logic of the technical feasibility analysis evaluation score is: Te score is the technical feasibility analysis and evaluation score, Re is the resource availability analysis and evaluation score, Co is the technical complexity analysis and evaluation score, and Ma is the maintenance difficulty analysis and evaluation score; When the technical feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the technical feasibility analysis is feasible; when the technical feasibility analysis evaluation score is less than the preset threshold, the result of the technical feasibility analysis is infeasible.

4. The customized product service method integrating user preferences according to claim 2, characterized in that: Perform economic feasibility analysis on all services in the service set according to the preset economic feasibility analysis algorithm, including: Performing expected benefit analysis, implementation cost analysis, and fund availability analysis on all services in the service set to obtain an expected benefit analysis evaluation score, an implementation cost analysis evaluation score, and a fund availability analysis evaluation score; The economic feasibility analysis evaluation score is calculated according to the expected benefit analysis evaluation score, the implementation cost analysis evaluation score and the capital availability analysis evaluation score, wherein the calculation logic of the economic feasibility analysis evaluation score is: E score is the economic feasibility analysis evaluation score, Be is the expected benefit analysis evaluation score, Ct is the implementation cost analysis evaluation score, and Af is the capital availability analysis evaluation score; When the economic feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the economic feasibility analysis is feasible; when the economic feasibility analysis evaluation score is less than the preset threshold, the result of the economic feasibility analysis is infeasible.

5. The customized product service method integrating user preferences according to claim 2, characterized in that: Perform time feasibility analysis on all services in the service set according to the preset time feasibility analysis algorithm, including: Perform development time analysis, time resource availability analysis, and time resource adaptability analysis on all services in the service set to obtain development time analysis evaluation scores, time resource availability analysis evaluation scores, and time resource adaptability analysis evaluation scores; The time feasibility analysis evaluation score is calculated according to the development time analysis evaluation score, the time resource availability analysis evaluation score and the time resource adaptability analysis evaluation score, wherein the calculation logic of the economic feasibility analysis evaluation score is: Ti score is the time feasibility analysis and evaluation score, Du is the development time analysis and evaluation score, Ta is the time resource availability analysis and evaluation score, and Ar is the time resource fit analysis and evaluation score; When the time feasibility analysis evaluation score is greater than or equal to a preset threshold, the result of the time feasibility analysis is feasible; when the time feasibility analysis evaluation score is less than the preset threshold, the result of the time feasibility analysis is infeasible.

6. The customized product service method integrating user preferences according to claim 1, characterized in that: Obtain user preference information based on user historical data, and use the preset perceived value model to score the perceived value of services in the service set, including: Obtain the number of times a service is used in the user's historical data, sort the services in descending order according to the number of times the services are used, and obtain a preset number of services and feature vectors of the services; The service feature vector is weighted according to the number of times the service is used, and the user preference vector is calculated; The similarity between the user preference vector and the feature vectors of the services in the service set is calculated to obtain a perceived value score, wherein the similarity of the feature vectors is calculated using the cosine similarity of the vectors.

7. A customized product service method integrating user preferences according to claim 6, characterized in that: The logic for constructing the service's feature vector includes: Obtain the service category and functional characteristics of the service, and use One-Hot encoding to convert the service category and functional characteristics into a numerical vector; The service category and the numerical vector of the functional characteristics are linked to obtain the characteristic vector of the service.

8. The customized product service method integrating user preferences according to claim 7, characterized in that: The service feature vector is weighted according to the number of times the service is used, and the user preference vector is calculated. The calculation logic is: U p is the user preference vector, n is the preset number, N i is the number of times the i-th service is used, N is the sum of the number of times the first n services are used, V i is the feature vector of the ith service.

9. A customized product service system integrating user preferences, characterized in that: include: Acquisition module: obtains all services of the product selected by the user and sets all services as a service collection; Analysis module: Perform feasibility analysis on all services in the service set according to the preset feasibility analysis algorithm, remove infeasible services, and update the service set; Scoring module: obtains user preference information based on user historical data, and uses a preset perceived value model to score the perceived value of services in the service set; Sorting module: Sort the services in the service set in descending order according to the perceived value score, and push the services to the user in order.

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