Assessment method for intelligent computing automation

Abstract

The invention provides an evaluation method for intelligent computing automation, and relates to the technical field of automatic demand analysis, and the method specifically comprises the steps: collecting information through an intelligent dialogue; automatically recommending an automatic tool; confirming by technicians; modifying by a technician; evaluating project implementation cost and income; automatically generating a report; through intelligent information collection, automatic tool recommendation, technician participation and automatic cost income analysis, the time and resource consumption of manual operation are remarkably reduced; through intelligent information processing and tool recommendation, the accuracy of the evaluation process is ensured, and the system calculates and predicts the project implementation cost through a financial model, predicts the actual benefits such as efficiency improvement and cost saving after project implementation, and provides a scientific decision basis for enterprises. And according to an analysis result, generating a feasibility report including project summary, cost and income analysis, risk assessment and other contents.

Description

Technical Field

[0001] The present invention relates to the technical field of automated demand analysis, and in particular to an intelligent computing automation evaluation method. Background Art

[0002] With the rapid development of information technology, automation technology is increasingly being used in enterprises. However, traditional automation tool evaluation methods suffer from inefficiencies and high costs, making them unable to meet enterprises' demand for intelligent and rapid solutions.

[0003] Currently, companies primarily assess whether their business is suitable for automation and the potential benefits of automation through offline assessments. During the project evaluation process, comprehensive project-related data is collected through various methods, including questionnaires, in-depth interviews, field observations, and comprehensive literature analysis. Subsequently, this data is analyzed in depth using statistical methods, content analysis techniques, and financial analysis techniques to extract key and valuable information. Finally, a project evaluation report is produced.

[0004] Amidst the growing digital transformation and adoption of automation tools, enterprises face significant challenges in quickly and accurately evaluating and selecting automation tools that meet their business needs, as well as scientifically assessing the costs and benefits of project implementation. Existing solutions often only address a subset of these needs, lacking systematicity and comprehensiveness, making it difficult to meet enterprises' deep-seated needs for intelligent, automated assessment tools. Traditional methods often struggle to quickly generate accurate assessment results, especially in projects involving complex business scenarios and diverse tool choices. This leads to unnecessary waste and risk during tool selection and implementation.

[0005] In the prior art, the publication number is CN107862423B, and the name is System Evaluation Method, Intelligent Evaluation System and Computer-readable Storage Medium; the system evaluation method includes: obtaining conversation records generated by the communication between the intelligent customer service system and the customer; statistically analyzing the semantic equivalence probability of each customer's questions, the number of conversation rounds for each customer, and the probability of the customer being transferred to manual customer service in the conversation records to obtain statistical data; and comprehensively evaluating the service level of the intelligent customer service system based on the statistical data to obtain an evaluation result. The present invention changes the manual evaluation method of the intelligent customer service system and adopts an automated system evaluation mechanism. Starting from the overall intelligent customer service system, it realizes an objective and comprehensive systematic evaluation of the intelligent customer service system, avoiding the subjectivity and curve limitations of manual evaluation, and obtaining a true and effective evaluation result of the service level of the intelligent customer service system, thereby improving the accuracy of the evaluation effect and feeding back the true service level of the intelligent customer service system, thereby improving the evaluation efficiency.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0007] The purpose of the present invention is to provide an intelligent computing and automated evaluation method to solve the problems raised in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] An intelligent computing automation evaluation method, comprising the following steps:

[0010] Intelligent dialogue information collection: Business information is entered through voice or text input, and the intelligent dialogue system automatically collects key parameters;

[0011] Automatically recommend automation tools: The intelligent dialogue system automatically matches appropriate automation tools based on collected key parameters;

[0012] Technical staff confirmation: Evaluate and confirm the automation tools recommended by the intelligent dialogue system;

[0013] Technical staff modification: Technical staff adjust or replace the recommended results of the automation tool according to actual conditions;

[0014] Project implementation cost and benefit assessment: The intelligent dialogue system integrates business information and automation tool options to conduct detailed cost and benefit analysis;

[0015] Automatic report generation: The intelligent dialogue system generates a feasibility report based on the analysis results, which includes a project overview, cost-benefit analysis, and risk assessment.

[0016] Furthermore, the specific steps of the intelligent dialogue to collect information are as follows:

[0017] Log in to the intelligent dialogue system, which guides users to enter business information through voice or text input;

[0018] The intelligent dialogue system receives business information input by users, parses and extracts key data, including the number of participants, single task processing time, frequency and number of task processing times, and unit labor cost;

[0019] The intelligent dialogue system verifies the integrity and accuracy of the data and prompts the user to supplement or correct any missing key data;

[0020] The intelligent dialogue system uses natural language processing technology to identify the business information entered by the user and automatically parse and extract the information;

[0021] The intelligent dialogue system records and stores the processed business information for use in subsequent steps.

[0022] Furthermore, the specific steps of the automatic recommendation automation tool are:

[0023] The intelligent dialogue system automatically matches the appropriate automation tools based on the collected key data;

[0024] The intelligent dialogue system generates recommendation results through algorithmic evaluation of the tool's functional modules, usage scenarios, and expected effects;

[0025] The intelligent dialogue system presents the recommendation results in a list to the technician for review;

[0026] The intelligent dialogue system uses a machine learning-based algorithm to score and match different automation tools to ensure that the tools are highly compatible with business needs;

[0027] The intelligent dialogue system records and stores the recommendation results for subsequent use.

[0028] Furthermore, the specific steps confirmed by the technicians are:

[0029] Technical personnel evaluate and confirm the automation tools recommended by the intelligent dialogue system, including the tool's functional modules, usage scenarios, and expected results;

[0030] Technical personnel will fully verify the applicability of recommended tools through functional demonstration, parameter setting, and actual business scenario testing;

[0031] If the technician is satisfied with the recommendation result, the output parameter is Y, and the project implementation cost and benefit evaluation is started; if not, the output parameter is N, and the technician modifies the project;

[0032] The technician records and stores the confirmation results for use in subsequent steps.

[0033] Furthermore, the specific steps modified by the technicians are as follows:

[0034] Technical personnel adjust or replace the automation tools recommended by the intelligent dialogue system based on actual business needs, including the automation tool version, tool quantity, and price parameters;

[0035] Technicians can optimize the recommendation results through tool library browsing, parameter configuration and customized development;

[0036] The technician records and stores the modified recommendation results for subsequent use;

[0037] After the modification is completed, return to the technician confirmation step for reconfirmation.

[0038] Furthermore, the specific steps for evaluating the project implementation costs and benefits are as follows:

[0039] The intelligent dialogue system integrates collected key data and automation tool options to conduct detailed cost-benefit analysis;

[0040] The intelligent dialogue system uses a financial model to calculate the estimated project implementation costs, including labor costs, equipment costs, and software costs;

[0041] The intelligent dialogue system uses the benefit analysis module to predict the actual benefits of efficiency improvement and cost savings after project implementation;

[0042] The system records and stores the analysis results for subsequent use.

[0043] Furthermore, the specific steps of automatically generating a report are as follows:

[0044] Based on the analysis results, the intelligent dialogue system generates a feasibility report that includes a project overview, cost-benefit analysis, and risk assessment.

[0045] The intelligent dialogue system sends the generated report to the decision maker via email or in-system notification;

[0046] The intelligent dialogue system records and stores the report generation and sending process for use in subsequent steps.

[0047] Furthermore, the calculation process of the machine learning algorithm for scoring and matching different automated tools is as follows:

[0048]

[0049] Among them, F i ∈[0,1] represents the score of functional module i, S j ∈[0,1] represents the score of usage scenario j, E k ∈[0,1] represents the score of the expected effect k, w f 、w s 、w e ∈[0,1] represents the weight coefficient of functional module, usage scenario and expected effect, w f +w s +w e =1, λ∈[0,1] represents the attenuation coefficient in the weighting function, which is used to balance the importance of different modules. n, m, and l represent the value ranges of the sequences l, j, and k of the functional modules, usage scenarios, and expected effects, respectively.

[0050] Furthermore, the financial model calculates the estimated project implementation cost as follows:

[0051] Total cost = w h × labor cost + w d × Equipment cost + w s × software cost + w o ×

[0052] other costs;

[0053] Where: w h ,w d ,w s ,w o ∈[0.2,0.8] represents the weight coefficient of manpower, equipment, software and other costs, satisfying w h +w d +w s +w o =1;

[0054] The calculation of the actual benefits after the project implementation predicted by the benefit analysis module is as follows:

[0055] Total revenue = e e ×Efficiency Improvement Benefit + e c × Total cost savings benefits;

[0056] Among them: e e ,e c ∈[0.2,0.8] represents the weight coefficient of efficiency improvement and cost saving, satisfying e e +e c =1.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] Through the design of core modules such as an intelligent dialogue system, automated tool recommendations, technician confirmation and modification, and cost-benefit analysis, this invention comprehensively addresses the pain points of enterprises in the process of evaluating and implementing automated tools, improves work efficiency, reduces implementation costs, and provides enterprises with efficient and accurate decision-making support.

[0059] The system uses financial models to calculate the estimated project implementation costs, including labor costs, equipment costs, and software costs, and predicts actual benefits such as efficiency improvements and cost savings after project implementation, providing companies with a scientific basis for decision-making. Based on the analysis results, the system generates a feasibility report containing a project overview, cost-benefit analysis, and risk assessment, and sends it to decision makers via email or in-system notifications to ensure the accuracy and actionability of the report content.

[0060] The present invention also significantly reduces the time and resource consumption of manual operations and improves the overall efficiency of the workflow through intelligent information collection, automated tool recommendation, technical personnel participation and automated cost-benefit analysis; by optimizing tool selection programs and scientifically evaluating project implementation costs, it helps companies avoid excessive investment or waste of resources and reduces implementation costs; through intelligent information processing and tool recommendation, it ensures the accuracy of the evaluation process and provides support for companies to make scientific decisions; the reports generated by the system are comprehensive and accurate, helping decision makers quickly understand the project situation and make scientific decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 Schematic diagram of the overall method of the present invention. DETAILED DESCRIPTION

[0062] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to specific embodiments.

[0063] It should be noted that, unless otherwise defined, the technical or scientific terms used in the present invention should have the usual meanings understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0064] Example 1:

[0065] See also Figure 1 The present invention provides a technical solution: an intelligent computing automation evaluation method, which specifically includes the following steps:

[0066] Intelligent dialogue information collection: Business information is entered through voice or text input, and the intelligent dialogue system automatically collects key parameters;

[0067] Automatically recommend automation tools: The intelligent dialogue system automatically matches appropriate automation tools based on collected key parameters;

[0068] Technical staff confirmation: Evaluate and confirm the automation tools recommended by the intelligent dialogue system;

[0069] Technical staff modification: Technical staff adjust or replace the recommended results of the automation tool according to actual conditions;

[0070] Project implementation cost and benefit assessment: The intelligent dialogue system integrates business information and automation tool options to conduct detailed cost and benefit analysis;

[0071] Automatic report generation: The intelligent dialogue system generates a feasibility report based on the analysis results, which includes a project overview, cost-benefit analysis, and risk assessment.

[0072] In this embodiment, preferably, the specific steps of collecting information through intelligent dialogue are as follows:

[0073] Log in to the intelligent dialogue system, which guides users to enter business information through voice or text input;

[0074] The intelligent dialogue system receives business information input by users, parses and extracts key data, including the number of participants, single task processing time, frequency and number of task processing times, and unit labor cost;

[0075] The intelligent dialogue system verifies the integrity and accuracy of the data and prompts the user to supplement or correct any missing key data;

[0076] The intelligent dialogue system uses natural language processing technology to identify the business information entered by the user and automatically parse and extract the information;

[0077] The intelligent dialogue system records and stores the processed business information for use in subsequent steps;

[0078] It's important to note that the specific steps involved in collecting information through intelligent dialogue utilize automation, natural language processing, data verification, and information storage. This significantly improves the efficiency and accuracy of information collection, reduces manual operations and data errors, and ensures the reliability of subsequent analysis and tool recommendations. Furthermore, the system supports multilingual and multi-platform input, enhancing its flexibility and applicability.

[0079] In this embodiment, preferably, the specific steps of the automatic recommendation automation tool are:

[0080] The intelligent dialogue system automatically matches the appropriate automation tools based on the collected key data;

[0081] The intelligent dialogue system generates recommendation results through algorithmic evaluation of the tool's functional modules, usage scenarios, and expected effects;

[0082] The intelligent dialogue system presents the recommendation results in a list to the technician for review;

[0083] The intelligent dialogue system uses a machine learning-based algorithm to score and match different automation tools to ensure that the tools are highly compatible with business needs;

[0084] The intelligent dialogue system records and stores the recommendation results for subsequent use;

[0085] It should be noted that the intelligent dialogue system automatically matches appropriate automation tools based on collected key data, reducing the time and effort of manual tool screening and evaluation. The intelligent dialogue system uses algorithms to evaluate the functional modules, usage scenarios, and expected effects of tools to generate recommendations, ensuring that the recommended tools are highly compatible with business needs. The intelligent dialogue system uses machine learning-based algorithms to score and match different automation tools, ensuring that the tools are highly compatible with business needs.

[0086] Through intelligent tool matching, algorithm evaluation, recommendation result presentation, machine learning scoring and recommendation result storage, the automatic tool recommendation process significantly improves the efficiency and accuracy of tool recommendations. It can automatically match tools according to business needs, generate scientific recommendation results through algorithm evaluation, and ensure the applicability and accuracy of recommendations through machine learning.

[0087] In this embodiment, preferably, the specific steps confirmed by the technicians are:

[0088] Technical personnel evaluate and confirm the automation tools recommended by the intelligent dialogue system, including the tool's functional modules, usage scenarios, and expected results;

[0089] Technical personnel will fully verify the applicability of recommended tools through functional demonstration, parameter setting, and actual business scenario testing;

[0090] If the technician is satisfied with the recommendation result, the output parameter is Y, and the project implementation cost and benefit evaluation is started; if not, the output parameter is N, and the technician modifies the project;

[0091] The technician records and stores the confirmation results for use in subsequent steps;

[0092] It should be noted that technical personnel conduct a comprehensive evaluation and confirmation of the functional modules, usage scenarios and expected effects of the recommended tools to ensure that the tools can truly meet business needs and reduce practical application problems caused by improper tool selection; the technical personnel confirmation steps significantly improve the reliability and applicability of tool recommendations through comprehensive evaluation of tool applicability, functional demonstration and actual test verification, flexible satisfaction confirmation, and record confirmation result storage; technical personnel can adjust and optimize the recommendation results according to actual needs to ensure that the final selected tools can meet business needs and achieve project goals.

[0093] In this embodiment, preferably, the specific steps modified by the technician are as follows:

[0094] Technical personnel adjust or replace the automation tools recommended by the intelligent dialogue system based on actual business needs, including the automation tool version, tool quantity, and price parameters;

[0095] Technicians can optimize the recommendation results through tool library browsing, parameter configuration and customized development;

[0096] The technician records and stores the modified recommendation results for subsequent use;

[0097] After the modification is completed, return to the technician confirmation step for reconfirmation;

[0098] It should be noted that technical personnel can adjust or replace the version, quantity and price parameters of automation tools according to actual business needs to ensure that the tools are highly matched with specific business scenarios; technical personnel's modification steps significantly improve the accuracy and applicability of tool recommendations through flexible tool adjustment, personalized optimization, information recording and reconfirmation, and support the efficient execution of subsequent project implementation; technical personnel can adjust and optimize the recommendation results according to actual business needs to ensure that the final selected tools can meet project requirements and achieve the expected results; at the same time, recording and storing the modified recommendation results avoids duplication of work and information loss, and enhances the technical personnel's collaborative efficiency and process consistency; the reconfirmation step further enhances the reliability of tool recommendations and ensures the accuracy and feasibility of the final recommendation results.

[0099] In this embodiment, preferably, the specific steps of the project implementation cost and benefit evaluation are as follows:

[0100] The intelligent dialogue system integrates collected key data and automation tool options to conduct detailed cost-benefit analysis;

[0101] The intelligent dialogue system uses a financial model to calculate the estimated project implementation costs, including labor costs, equipment costs, and software costs;

[0102] The intelligent dialogue system uses the benefit analysis module to predict the actual benefits of efficiency improvement and cost savings after project implementation;

[0103] The system records and stores the analysis results for subsequent use;

[0104] It should be noted that the intelligent dialogue system integrates key data (such as the number of participants, single task processing time, frequency and number of task processing times, unit labor cost, etc.) and automated tool options to provide a comprehensive cost-benefit analysis view. The intelligent dialogue system uses financial models to calculate the estimated project implementation costs, including core project costs such as labor costs, equipment costs, and software costs. The intelligent dialogue system uses the benefit analysis module to predict the actual benefits of efficiency improvements and cost savings after project implementation, combining business data and tool usage results to provide scientific benefit forecasts.

[0105] The project implementation cost and benefit assessment steps integrate core functions such as data and tool options, financial model cost calculation, benefit analysis module benefit prediction, and information storage through an intelligent dialogue system, significantly improving the comprehensiveness, accuracy, and efficiency of project assessments. The system can provide scientific cost forecasts and benefit analyses based on actual business data and tool selections, helping companies comprehensively assess the economic viability and feasibility of projects. At the same time, the analysis results are recorded and stored to support subsequent processes, avoiding duplication of work and information loss, and enhancing the consistency and reliability of the entire assessment process.

[0106] In this embodiment, preferably, the specific steps of automatically generating a report are as follows:

[0107] Based on the analysis results, the intelligent dialogue system generates a feasibility report that includes a project overview, cost-benefit analysis, and risk assessment.

[0108] The intelligent dialogue system sends the generated report to the decision maker via email or in-system notification;

[0109] The intelligent dialogue system records and stores the report generation and sending process for use in subsequent steps;

[0110] It should be noted that the intelligent dialogue system automatically generates a feasibility report based on the analysis results, which includes project overview, cost-benefit analysis, risk assessment, etc., reducing the time and effort of manual report writing.

[0111] The specific steps of automatic report generation significantly improve the efficiency and accuracy of enterprises in the report generation and transmission process through the advantages of automated report generation, convenient report sending, information recording and storage, standardized report content, reduction of human errors, and support for decision makers to make quick decisions. The system can reduce manual labor, ensure the accuracy and consistency of report content, and support decision makers to quickly obtain key information and make scientific decisions.

[0112] In this embodiment, preferably, the calculation process of the machine learning algorithm for scoring and matching different automation tools is as follows:

[0113]

[0114] Among them, F i ∈[0,1] represents the score of functional module i, S j ∈[0,1] represents the score of usage scenario j, E k ∈[0,1] represents the score of the expected effect k, w f 、w s 、w e ∈[0,1] represents the weight coefficient of functional module, usage scenario and expected effect, w f +w s +w e =1, λ∈[0,1] represents the attenuation coefficient in the weighting function, which is used to balance the importance of different modules. n, m, and l represent the value ranges of the sequences l, j, and k of the functional modules, usage scenarios, and expected effects, respectively.

[0115] It should be noted that when the function module score F i The higher the value, the stronger the applicability of the tool in this module; the usage scenario score S j The higher the value, the better the applicability of the tool in the scenario; the expected effect score E k The higher the value, the better the tool performs under this effect. f 、w s 、w e Dynamically adjust according to business needs to ensure the balance and flexibility of score calculation. The decay coefficient λ controls the impact of different module scores on the total score to prevent a single module from dominating.

[0116] When the output approaches 1, it indicates that the tool is a good fit for the business requirements in all aspects, and the recommendations are reliable and risk-free. When the output approaches 0, it indicates that the tool does not match the business requirements in some key aspects and may need to be adjusted or eliminated. The value range is limited to [0, 1] to ensure intuitive and actionable scoring results and avoid inapplicability caused by excessively large or small values.

[0117] In this embodiment, preferably, the financial model calculates the estimated project implementation cost as follows:

[0118] Total cost = w h × labor cost + w d × Equipment cost + w s × software cost + w o ×

[0119] other costs;

[0120] Where: w h ,w d ,w s,w o ∈[0.2,0.8] represents the weight coefficient of manpower, equipment, software and other costs, satisfying w h +w d +w s +w o =1;

[0121] The calculation of the actual benefits after the project implementation predicted by the benefit analysis module is as follows:

[0122] Total revenue = e e ×Efficiency Improvement Benefit + e c × Total cost savings benefits;

[0123] Among them: e e ,e c ∈[0.2,0.8] represents the weight coefficient of efficiency improvement and cost saving, satisfying e e +e c =1;

[0124] It should be noted that the above formula can clearly calculate the total cost and total benefit of a project, and evaluate the technical effectiveness based on the output value range. The formula design has high mathematical complexity and academic depth, which can meet the practical needs of financial models and reflect technical and theoretical innovations.

[0125] When the formula output approaches 0, it indicates that there are serious problems with the project cost and benefit analysis results, and it may be necessary to re-evaluate the project plan or optimize resource allocation.

[0126] When the formula output approaches 1, it means that the project cost and benefit analysis results are good and the project implementation is highly efficient and economical.

[0127] It should be noted that: All calculation formulas in this application document use regression analysis including but not limited to machine learning algorithms to deeply analyze the relevant parameters collected and identify their natural trends and relationships. Use professional software, such as Python's Scikit-learn library or R language, to automatically generate mathematical models that match the data. Then, objectively evaluate the performance of the model through methods such as cross-validation, and combine continuous feedback and optimization to ensure that the created formula truly reflects the inherent laws of the data, thereby ensuring its effectiveness and accuracy. In all calculation formulas in this application, the parameters in each formula are dimensionally non-dimensionalized within a consistent range to ensure that different physical quantities are compared on the same scale; dimensionless technical means include but are not limited to Min-Max Normalization and Z-Score standardization;

[0128] The technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0129] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0130] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0131] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent computing automated evaluation method, characterized in that: The specific steps include: Intelligent dialogue information collection: Business information is entered through voice or text input, and the intelligent dialogue system automatically collects key parameters; Automatically recommend automation tools: The intelligent dialogue system automatically matches appropriate automation tools based on collected key parameters; Technical staff confirmation: Evaluate and confirm the automation tools recommended by the intelligent dialogue system; Technical staff modification: Technical staff adjust or replace the recommended results of the automation tool according to actual conditions; Project implementation cost and benefit assessment: The intelligent dialogue system integrates business information and automation tool options to conduct detailed cost and benefit analysis; Automatic report generation: The intelligent dialogue system generates a feasibility report based on the analysis results, which includes a project overview, cost-benefit analysis, and risk assessment.

2. The intelligent computing and automated evaluation method according to claim 1, characterized in that: The specific steps of collecting information through intelligent dialogue are as follows: Log in to the intelligent dialogue system, which guides users to enter business information through voice or text input; The intelligent dialogue system receives business information input by users, parses and extracts key data, including the number of participants, single task processing time, frequency and number of task processing times, and unit labor cost; The intelligent dialogue system verifies the integrity and accuracy of the data and prompts the user to supplement or correct any missing key data; The intelligent dialogue system uses natural language processing technology to identify the business information entered by the user and automatically parse and extract the information; The intelligent dialogue system records and stores the processed business information for use in subsequent steps.

3. The intelligent computing and automated evaluation method according to claim 2, characterized in that: The specific steps of the automatic recommendation automation tool are: The intelligent dialogue system automatically matches the appropriate automation tools based on the collected key data; The intelligent dialogue system generates recommendation results through algorithmic evaluation of the tool's functional modules, usage scenarios, and expected effects; The intelligent dialogue system presents the recommendation results in a list to the technician for review; The intelligent dialogue system uses a machine learning-based algorithm to score and match different automation tools to ensure that the tools are highly compatible with business needs; The intelligent dialogue system records and stores the recommendation results for subsequent use.

4. The intelligent computing and automated evaluation method according to claim 3, characterized in that: Specific steps confirmed by the technicians: Technical personnel evaluate and confirm the automation tools recommended by the intelligent dialogue system, including the tool's functional modules, usage scenarios, and expected results; Technical personnel will fully verify the applicability of recommended tools through functional demonstration, parameter setting, and actual business scenario testing; If the technician is satisfied with the recommendation result, the output parameter is Y, and the project implementation cost and benefit evaluation is started; if not, the output parameter is N, and the technician modifies the project; The technician records and stores the confirmation results for use in subsequent steps.

5. The intelligent computing and automated evaluation method according to claim 4, characterized in that: The specific steps modified by the technicians are as follows: Technical personnel adjust or replace the automation tools recommended by the intelligent dialogue system based on actual business needs, including the automation tool version, tool quantity, and price parameters; Technicians can optimize the recommendation results through tool library browsing, parameter configuration and customized development; The technician records and stores the modified recommendation results for subsequent use; After the modification is completed, return to the technician confirmation step for reconfirmation.

6. The intelligent computing and automated evaluation method according to claim 5, characterized in that: The specific steps for evaluating the project implementation costs and benefits are as follows: The intelligent dialogue system integrates collected key data and automation tool options to conduct detailed cost-benefit analysis; The intelligent dialogue system uses a financial model to calculate the estimated project implementation costs, including labor costs, equipment costs, and software costs; The intelligent dialogue system uses the benefit analysis module to predict the actual benefits of efficiency improvement and cost savings after project implementation; The system records and stores the analysis results for subsequent use.

7. The intelligent computing and automated evaluation method according to claim 6, characterized in that: The specific steps of automatically generating a report are as follows: Based on the analysis results, the intelligent dialogue system generates a feasibility report that includes a project overview, cost-benefit analysis, and risk assessment. The intelligent dialogue system sends the generated report to the decision maker via email or in-system notification; The intelligent dialogue system records and stores the report generation and sending process for use in subsequent steps.

8. The intelligent computing and automated evaluation method according to claim 7, characterized in that: The calculation process of the machine learning algorithm for scoring and matching different automated tools is as follows: Among them, F i ∈[0,1] represents the score of functional module i, S j ∈[0,1] represents the score of usage scenario j, E k ∈[0,1] represents the score of the expected effect k, w f 、w s 、w e ∈[0,1] represents the weight coefficient of functional module, usage scenario and expected effect, w f +w s +w e =1, λ∈[0,1] represents the attenuation coefficient in the weighting function, which is used to balance the importance of different modules. n, m, and l represent the value ranges of the sequences l, j, and k of the functional modules, usage scenarios, and expected effects, respectively.

9. The intelligent computing and automated evaluation method according to claim 6, characterized in that: The financial model calculates the estimated project implementation costs as follows: Total cost = w h × labor cost + w d × Equipment cost + w s × software cost + w o × other costs; Where: w h ,w d ,w s ,w o ∈[0.2,0.8] represents the weight coefficient of manpower, equipment, software and other costs, satisfying w h +w d +w s +w o =1; The calculation of the actual benefits after the project implementation predicted by the benefit analysis module is as follows: Total revenue = e e ×Efficiency Improvement Benefit + e c × Total cost savings benefits; Among them: e e ,e c ∈[0.2,0.8] represents the weight coefficient of efficiency improvement and cost saving, satisfying e e +e c =1.

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