42 results about "Business goals" patented technology

The invention discloses a water conservancy operation and maintenance platform based on a digital twinning technology, and relates to the technical field of digital twinning, and the platform comprises a digital twinning model building unit which is used for building a water conservancy facility digital twinning model comprising a physical mechanism model; the health state evaluation unit is used for calculating theoretical performance based on the mechanism model and comparing the theoretical performance with actual performance to obtain a performance residual error so as to accurately quantify the health state of the equipment; the intelligent scheduling decision-making unit adopts a reinforcement learning framework, performs decision-making deduction by using a composite reward function fusing business rewards and quantitative health loss cost in a simulation environment associated with digital twinning, and generates an optimal scheduling instruction giving consideration to business targets and equipment long-term health; and the closed-loop control and feedback unit is used for executing the instruction and forming a dynamic optimization closed loop. According to the method, abstract health loss is converted into computable decision cost, and global optimization of an operation and maintenance strategy is realized.

The invention discloses a micro-service full-link gray level traffic management system and method based on PaaS, and relates to the field of traffic management, and the system comprises an intelligent traffic analysis and decision center module, a micro-service arrangement and management platform, a full-link data analysis module, a dynamic safety protection and compliance auditing module, and a distributed configuration center. According to the micro-service full-link gray flow management system and method based on the PaaS, dynamic self-adaptive gray strategy formulation can be carried out, the latest service target, the gray version release plan and the system performance index threshold can be synchronously obtained in cooperation with a distributed configuration center, and the flow management efficiency is improved based on the information and the intelligent screening result of the flow. A routing strategy and a version switching strategy of gray traffic can be dynamically generated, and in the strategy making process, the real-time load condition of a system, the availability of micro-services and key index changes of services are fully considered.

A non-transitory computer readable medium having computer instructions stored therein that when executed by a computer system cause the computer system to perform operations including receiving a first user input defining a dialog session comprising one or more steps of a natural language conversation flow, receiving a second user input defining a positive outcome of the dialog session, receiving, via a chat interface, a natural language input, initiating the dialog session in response to an association between the natural language input and the dialog session, receiving, via the chat interface, a subsequent natural language input, and updating a data entry associated with the custom metric in an outcome log in response the subsequent natural language input being indicative of the positive outcome of the dialog session.

The invention discloses a generative dialogue optimization method and system based on multi-step intensified simulation, and the method comprises the steps: generating a plurality of candidate replies based on the current dialogue history through a basic dialogue model; using the user simulator to generate a dialogue chain for each candidate reply; calculating a reward for each dialogue chain, selecting K dialogue chains with the highest reward value as high-quality samples, and taking the dialogue chain with the lowest reward value as a negative sample; updating parameters of the basic dialogue model by using the high-quality sample and the negative sample through a contrast learning and reinforcement learning method to obtain a trained basic dialogue model as a customer service model; and the customer service model generates a reply according to a statement input by the user. According to the conversation generation method, multi-round conversation dynamic planning, medical scene adaptability optimization and efficient strategy exploration can be fused, and double optimization of user trust establishment and business goal achievement is achieved while compliance is ensured.

The embodiments herein are directed to a system and method for business data mapping which are characterized by the use of denormalized metadata. The system and method operate upon heterogeneous data sets in comparison to one or more business-specific glossaries. The returned data sets are characterized by adherence to business goals, and are dynamically available to an end-user with little to no specialized coding infrastructure.

A system and method are disclosed for performing rough cut capacity planning. The method includes receiving supply chain transaction data as transaction tables, generating a base plan and generating updated transaction tables, denormalizing the base plan and the updated transaction tables, generating supply chain network flow paths and supply chain network data, solving a rough cut capacity planning problem based at least in part on the supply chain network flow paths, the supply chain network data and simulation data, repeating at least the generating and solving until business goals of the rough cut capacity planning meet a threshold, and updating the simulation data based on an upsert process. The method further includes relaxing supply chain network constraints, inverting the supply chain network, and traversing a perturbation in the supply chain network constraints as demands in a reverse direction towards customer nodes.

The invention discloses an intelligent test data generation and optimization method and system based on a low-code platform, and belongs to the technical field of software engineering and artificial intelligence, and the method comprises the steps: analyzing a business rule and data model definition information of a low-code application; according to the business rule and the data model definition information, utilizing a generative model to generate initial test data; performing quality evaluation and fault prediction on the generated initial test data; collecting test execution feedback information, including fault types caused by data, performance bottleneck positions and the like; formulating a data generation parameter adjustment strategy according to the test execution feedback information and the service target; and regenerating test data according to the adjustment strategy, and outputting the optimized test data for a subsequent iterative test. And the optimized test data is subjected to effect evaluation, so that the test quality and efficiency are continuously improved. According to the invention, the test data dynamically adapts to business demand changes, the test coverage rate and the fault discovery efficiency are improved, and the labor cost is reduced.

The invention discloses a high-intention potential customer mining method and system fusing ensemble learning and CNN deep learning. The method comprises the following steps: acquiring original data of user ordering information, and processing and analyzing the original data; analyzing a business target, and performing feature engineering on the data to obtain a full-quantity feature set; respectively establishing a LightGBM ensemble learning model and a Random Forest ensemble learning model, obtaining evaluation indexes and total feature information output by the two ensemble learning models, and analyzing output results of the two ensemble learning models to obtain a final important feature set; establishing a CNN deep learning model for predicting the submersible guests; screening pseudo high potential users from historical data of point marketing; and filtering the pseudo high potential users by using the predicted potential guests output by the CNN deep learning model to obtain final potential guest information. According to the scheme, a large amount of data can be automatically processed, data assets are comprehensively mined and utilized, and the comprehensiveness and accuracy of decision making are improved.

Pre-trained large language models may be trained on a large data set which may not necessarily align with specific tasks, business goals, and requirements. Pre-trained large language models can solve generic semantic relationship or question-answering type problems but may not be suited for content item retrieval or recommendation of content items that are semantically relevant to a query. It is possible to build a machine learning model while using transfer learning to learn from pre-trained large language models. Training data can significantly impact the performance of machine learning models, especially machine learning models developed using transfer learning. The training data can impact a model's performance, generalization, fairness, and adaptation to specific domains. To address some of these concerns, a popularity bucketing strategy can be implemented to debias training data. Optionally, an ensemble of models can be used to generate diverse training data.

The present application relates to a kind of intelligent interview evaluation and feedback system based on multi-modal data fusion, specifically relates to data processing field, by meta-learning mechanism dynamic perception interview scene and generate initial fusion weight, subsequently utilize the complex interaction relationship between modalities modeled by graph neural network to carry out fine-grained correction to weight, so as to significantly improve the accuracy and scene adaptability of multi-modal evaluation, further introduce reinforcement learning, link evaluation decision and long-term performance of talents, continuously optimize weight generation strategy, ensure that evaluation standard and business goal are aligned, finally, through closed-loop iteration mechanism, make the whole scheme can be updated automatically according to new data and performance feedback, continuous evolution, with strong self-optimizing ability and long-term robustness, realize the fundamental change from static rule to dynamic intelligent decision.

The invention provides an application program monitoring method and system, and relates to the technical field of information, the processing flow of each request response is tracked in detail and the abnormity is detected through a constructed time sequence model and a log detection model, the performance bottleneck and the fault point in an application program can be quickly positioned, and the reliability of the application program is improved. The stable monitoring guarantee of the user according to the own service target and the own platform is realized, so that the stability of the application program is improved, and the user experience is improved.

The present invention relates to big data technology, and discloses a method for attribution analysis of business events, including: obtaining behavioral data of sample users of preset business events to obtain a sample data set; determining target attention events according to preset event categories and business goals; selecting data that has a forward association with the target attention events from the sample data set according to the preset event categories to obtain impact events; performing attribution analysis on the impact events to obtain analysis results; and determining an optimized business strategy for the business goals based on the analysis results. In addition, the present invention also relates to blockchain technology, and the behavioral data of the sample users can be stored in a node of the blockchain. The present invention also proposes an attribution analysis device, an electronic device, and a computer-readable storage medium for business events. The present invention can solve the problem of lack of behavioral motivation analysis of business events and poor analysis results.

The invention discloses an e-commerce advertisement putting strategy generation method and system based on quantum computing optimization, and particularly relates to the technical field of quantum computing, comprising parameter coding, quantum optimization, line evolution, strategy resolving, dynamic optimization and strategy verification and output. According to the method, a high-dimensional parallel search mechanism based on a parameterized quantum circuit is constructed by introducing a quantum calculation normal form, the problem of calculation complexity index increase of a classical computer in e-commerce advertisement multi-parameter combination optimization is effectively solved, and the multi-parameter combination optimization of e-commerce advertisements is realized by designing a classical and quantum mixed architecture and a dynamic feedback optimization mechanism. The real-time adaptive adjustment of the advertisement putting strategy is realized, the practicability and robustness of the system are remarkably improved, the precise alignment of the technical means and the commercial target is realized by deeply coupling the quantum optimization process with the specific e-commerce advertisement business index, and a quantifiable business improvement effect is provided.

A robot system comprises: a robot configured to perform a predefined operation; and a controller configured to receive a Direct Teaching instruction manually from a user to teach the robot an operational goal and to control the robot's operation.The controller performs an adaptation control of a parameter to determine a manipulation perception in Direct Teaching and is configured such that, during the adaptation control, it: acquires the parameter regarding the manipulation perception and a predefined rating index based on the result of the user's instigation to manually perform a specific task operation with respect to the robot; calculates a score based on the rating index, which is a mechanical rating for the task operation, and presents the score to the user; and changes the parameter depending on a subjective rating regarding the manipulation perception by the user.

The invention belongs to the technical field of intelligent factories, and particularly relates to an AI technology-based intelligent steel factory and a construction method thereof. The construction method comprises the steps that industrial robots are arranged in a raw material area, an area before iron making, a steelmaking area, a steel rolling area, a finishing operation area and an inspection and test area of a steel factory; performing unified standardization and quantification on related factors compiled by the production plan to form a factor library and a material type library; setting an optimization control system of various specific business targets; constructing an intelligent database of the steel factory, namely summarizing data information in the whole range of the steel factory into the intelligent database of the steel factory; establishing a production operation management and control platform based on an AI technology, and performing data extraction, cleaning and classified storage on the intelligent database of the steel factory; and intelligent personnel and material scheduling is carried out according to the production operation management and control platform. Through the application of the AI algorithm and in combination with the process standard, the plan yield and the plan making efficiency are improved, the application of the control model is optimized, and the quality consistency management and control is promoted.

This invention provides an artificial intelligence-based software refactoring method. The method includes: acquiring the current code data and user data of the software to be refactored; determining a target refactoring strategy based on the current code data and user data; generating refactoring code data corresponding to the target refactoring strategy based on a large language model; and refactoring the software based on the refactoring code data to obtain the target software. This invention analyzes code data and user data, considering both the code problems of the software to be refactored and user business expectations, to generate a target refactoring strategy that balances technical optimization and business needs. This avoids the problem of the separation between technical optimization and business goals in traditional methods, ensuring that the refactored code accurately matches the user's actual business scenario while optimizing technical indicators, reducing the cost of secondary modifications due to misunderstandings of requirements, and thus improving the accuracy and efficiency of software refactoring.

1. Name of the Design Product: Graphical User Interface for Displaying Business Goal Completion Status for Electronic Devices. 2. Use of the Design Product: An electronic device. 3. Design Key Points of the Design Product: Lies in the content of the graphical user interface on the screen. 4. Picture or Photograph Most Indicating the Design Key Points: The front view of Design 1. 5. As it is a common design, the rear views, left views, right views, top views and bottom views of Design 1 to Design 3 are omitted. 6. Design 1 is designated as the basic design. 7. Use of the Graphical User Interface: A graphical user interface for displaying business goal completion status, facilitating users to view the goal completion status of the current business, and helping users intuitively understand the progress of the tasks being carried out; Click on Card 01 of Task 1 in the front view of Design 1 to enter the interface change state diagram of Design 1; Stay at the front view of Design 2 for a preset time to enter Interface Change State Diagram 1 of Design 2, stay at Interface Change State Diagram 1 of Design 2 for a preset time to enter Interface Change State Diagram 2 of Design 2, stay at Interface Change State Diagram 2 of Design 2 for a preset time to enter Interface Change State Diagram 3 of Design 2, stay at Interface Change State Diagram 3 of Design 2 for a preset time to enter Interface Change State Diagram 4 of Design 2; The front view of Design 2, Interface Change State Diagram 1 of Design 2, Interface Change State Diagram 2 of Design 2, Interface Change State Diagram 3 of Design 2 and Interface Change State Diagram 4 of Design 2 are dynamic pattern changes showing the coherent display of Card 01 of Task 1 from the unpassed state to the passed state when the system recognizes the user's current data and determines that the user has completed Task 1; Click on Card 01 of Task 1 in the front view of Design 3 to enter the interface change state diagram of Design 3. 8. Other Situations Requiring Explanation: Other Explanation: The gray part in the graphical user interface of this design product is the content screen. For example, the gray circle and the gray rectangle part are user avatars or pictures; The X part in the graphical user interface of this design product is variable or belongs to the content screen. For example, X represents text and / or numbers.

The invention relates to a marketing decision system driven by multi-source data, and relates to the technical field of artificial intelligence, and the system comprises a state sensing module which is used for determining user state information representing the current state of a user according to the real-time interaction behavior of the user collected on terminal equipment; the intention acquisition module is used for acquiring marketing intention information representing a commercial target; the content generation module is used for dynamically generating marketing content by utilizing a generative model in response to the user state information and the marketing intention information; and the content presentation module is used for presenting the dynamically generated marketing content on an interface of the terminal equipment. According to the method and the device, the dynamic change of the user in a specific situation can be captured more accurately and more timely, so that the matching degree of the marketing content and the instant state of the user is remarkably improved, the accuracy and the real-time performance of a marketing decision are enhanced, and the flexibility and the intelligent level of the marketing decision are improved.

The present invention relates to the field of human resources technology, and specifically to a human resources intelligent allocation and optimization system, which includes a career analysis and prediction module, a career path planning module, an emergency deployment management module, and a human resources optimization module. The present invention realizes the accurate prediction and dynamic deployment of career paths by integrating the career history and skill data of medical staff. The precise career transition point analysis makes talent matching more accurate and reduces resource waste. The career training recommendations customized for the hospital's business goals improve the pertinence and effectiveness of training, optimize the talent training process, and improve the training effect of professional talents. In an emergency, the system can respond in time through real-time data monitoring and conduct rapid and effective manpower deployment to ensure that the hospital can maintain efficient operation in the face of emergency medical needs. Through continuous data updates and feedback, the human resources allocation strategy is continuously optimized, which improves the hospital's adaptability and management efficiency in a changing environment.

A non-transitory computer readable medium having computer instructions stored therein that when executed by a computer system cause the computer system to perform operations including receiving a first user input defining a dialog session comprising one or more steps of a natural language conversation flow, receiving a second user input defining a positive outcome of the dialog session, receiving, via a chat interface, a natural language input, initiating the dialog session in response to an association between the natural language input and the dialog session, receiving, via the chat interface, a subsequent natural language input, and updating a data entry associated with the custom metric in an outcome log in response the subsequent natural language input being indicative of the positive outcome of the dialog session.

The invention relates to the technical field of data analysis, and particularly discloses an information pushing method and device, computer equipment and a storage medium. The information management platform uniformly manages generation and pushing of the activity information, generates the activity information and the activity participation rule according to the activity information generation model and the matching rule generation model, intelligently matches the users capable of participating in the activity according to the activity participation rule, does not need to independently manage the activity corresponding to each service, does not need manual participation, and improves the user experience. And matching can be performed according to the basic information of the user and the activity participation rule, and the activity information is pushed to the user meeting the rule, so that the generation efficiency of the activity information and the pushing accuracy of the activity information are improved. The method is applied to businesses such as financial insurance sales and medical health information popularization, optimal activity information corresponding to the businesses can be intelligently generated, the optimal activity information is accurately pushed to users meeting participation rules, and the business goal is effectively achieved.

The invention belongs to the technical field of intelligent logistics, and particularly relates to a logic processing method, system and device for an intelligent question and answer model in a freight scene and a medium, and the method comprises the steps: when a user initiates a dialogue, analyzing a business target according to the dialogue content of the user; performing multiple rounds of conversations with the user based on the business target, and collecting related information of the business target from the multiple rounds of conversations; wherein for each round of dialogue of the user, the correlation between the current dialogue content and the service target is evaluated: if the dialogue content is not related to the service target, a chat mode is started to call corresponding data information in a database to make a reply according to the demand of the user; and if the dialogue content is related to the business target, collecting and updating the related information of the business target, and re-evaluating the information collection completion degree of the business target after the information collection completion degree of the business target so as to perform reflection according to the information collection completion degree of the business target and confirm whether a user needs to be guided to provide the related information of business target missing.

The purpose of the present application is to provide a method, device, medium and program product for determining a magic number, the method comprising: determining one or more first indicator features corresponding to a business goal based on product function information of a target application and historical behavioral performance information of a user; evaluating the one or more first indicator features based on statistical results corresponding to multiple dimensions, and determining at least one second indicator feature from the one or more first indicator features based on the evaluation results, wherein the multiple dimensions include a user quantity scale dimension and a historical business effect dimension; inputting at least one second indicator feature into a predetermined feature evaluation model to obtain importance information corresponding to the one or more second indicator features, and determining one or more target indicator features from the one or more second indicator features based on the importance information; determining critical value information corresponding to the one or more target indicator features, and using the critical value information as the magic number corresponding to the business goal.

An implementation method, device and equipment for path searching along an original path as much as possible and a storage medium. In the application, the business goal of "searching along the original path as much as possible" is converted into a quantifiable priority index in the path searching algorithm. By judging the "deviation" degree of the candidate route from the original route in real time during the path searching process, and giving a lower priority to the route that deviates earlier, the search process is systematically guided to preferentially explore the route branch similar to the original path, and the optimal solution is efficiently found.

This invention relates to a dialogue goal optimization device, method, and program for optimizing goal achievement in user interactions. Based on user utterances and actions, it estimates user states, including emotions, resistance, comprehension, and signs of detachment, as well as goal progress indicating the degree of achievement of primary and sub-goals, and maps these to a state space. After restricting the set of candidate response strategies based on constraints such as compliance and cost applied to the dialogue, it selects a response strategy that maximizes the objective function. Furthermore, it performs a self-correction process that dynamically updates the parameters of the response strategy in response to signs of failure detected during the dialogue. This makes it possible to suppress user detachment while adhering to practical constraints and continuously improve the business goal achievement rate.

A method for generating instructions for maintaining goals includes integrating a control center system with multiple healthcare provider data systems and obtaining information from the healthcare provider data systems. The method can then use artificial intelligence to correlate the obtained information with identified business goals of a donation center and use a heuristic model to generate instructions to the donation center to achieve the identified business goals. The method can then present the instructions to a user and / or user system so that the instructions can be executed.

A system and method are disclosed for performing rough cut capacity planning. The method includes receiving supply chain transaction data as transaction tables, generating a base plan and generating updated transaction tables, denormalizing the base plan and the updated transaction tables, generating supply chain network flow paths and supply chain network data, solving a rough cut capacity planning problem based at least in part on the supply chain network flow paths, the supply chain network data and simulation data, repeating at least the generating and solving until business goals of the rough cut capacity planning meet a threshold, and updating the simulation data based on an upsert process. The method further includes relaxing supply chain network constraints, inverting the supply chain network, and traversing a perturbation in the supply chain network constraints as demands in a reverse direction towards customer nodes.

The invention relates to the technical field of service self-learning, and discloses an alarm false alarm reduction system and method based on service self-learning, and the method comprises the following steps: obtaining a task index and resource time sequence data in a service change log, and carrying out the service intention perception based on the task index and the resource time sequence data; obtaining a forward feature of business intention perception, and obtaining a reverse feature based on manual annotation and a weight reduction feature of adversarial training weight reduction; and constructing a learning cooperative training model according to the forward feature, the reverse feature and the weight reduction feature. According to the method, task indexes and resource time sequence data in a business change log are analyzed, BERT semantic recognition and LSTM periodic analysis technologies are combined, and an intention vector of a quantitative business target is dynamically generated. According to the method, the limitation of a static alarm threshold value is overcome, and the system can sense the real intention of service operation in real time, so that normal service fluctuation and real abnormity are distinguished more accurately, and the false alarm rate caused by service scene change is remarkably reduced.

The invention discloses a business personnel allocation method and device, electronic equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining a matched business prediction model according to a business target; sending the customer set and the business personnel set to a business prediction model so as to obtain a prediction distribution result through the business prediction model; and according to the business target and the business constraint set, analyzing the prediction distribution result through a decision planning method, and distributing a corresponding business person for each client. According to the technical scheme provided by the embodiment of the invention, the distribution efficiency of the business personnel is improved, the labor cost and the time cost consumed by the distribution of the business personnel are reduced, the matching degree between the business personnel and the clients is improved, and the smooth communication between the business personnel and the clients is ensured.

The invention discloses an electronic information security storage system and method based on cloud computing, and relates to the technical field of security storage, by introducing a behavior log and enterprise mode conjoint analysis mechanism in the step S1, the system can perform scene division and label classification on user operation behaviors, and comprehensive description of behavior semantics in a multi-dimensional context is realized. In the step S2, by constructing similarity analysis of a service semantic vector and a behavior semantic vector and combining a user behavior trajectory similarity matrix, dynamic judgment of the matching degree between the user access behavior and a service target is achieved, so that an intention judgment result with high credibility is obtained, and the recognition rate of the hidden abnormal behavior is further improved. And S3, performing comparative analysis on the intention credibility under the scene label and a dynamic credibility threshold, generating a sub-scene risk level index, and performing back-stepping on a replica redundancy control strategy in combination with behavior log data, thereby effectively suppressing the problem of redundant replica diffusion.