208 results about "User expectations" patented technology

The invention discloses an automatic large language model selection method based on multi-dimensional evaluation and dynamic weight adjustment, and aims to solve the problems of low text generation quality, inaccurate dialogue questions and answers, low online assistant task completion rate and the like in an existing large language model by introducing a multi-dimensional evaluation mechanism. According to the method, a plurality of evaluation dimensions such as ROUGE index evaluation, text quality evaluation, semantic similarity evaluation, safety compliance evaluation, front suitability evaluation, question and answer evaluation, dialogue evaluation, online customer service evaluation and online assistant evaluation are comprehensively considered, the performance of the large language model is comprehensively evaluated, and through analysis of operation data and user feedback, the evaluation accuracy of the large language model is improved. And dynamically adjusting the weight of each evaluation dimension to adapt to continuously changing application requirements and user expectations. And finally, according to the comprehensive score, an optimal large language model is automatically selected, and high quality and user satisfaction of Web services are ensured.

The invention provides a multi-modal RAG knowledge question answering method and device applied to the vertical field, relates to the technical field of artificial intelligence, supports multi-modal input of to-be-answered texts including texts, pictures, audios and videos, and makes full use of semantic information of multi-modal data. And utilizing a plurality of preset retrieval models to retrieve the knowledge fragments corresponding to the to-be-answered text to obtain a plurality of retrieval results. Various retrieval results are fused through an RRF algorithm, and scores are calculated by using a target reordering model for reordering, so that the recall rate is improved. And based on the retrieval content and the preset knowledge frequency information, fine tuning sorting is further carried out, so that the method is more accurate and meets user expectation. According to the method, the natural language understanding ability of a large language model, a target reward model and related information recalled by the RAG are combined to generate optimal solution data, and meanwhile, a target scoring model and domain expert knowledge are utilized to provide more professional high-quality solution data meeting actual requirements.

Provided are a video generation method, an electronic device, and a computer readable storage medium, relating to the technical fields of computers and video processing. The video generation method comprises: acquiring a target text, wherein the target text is used for describing video content to be generated (S21); and using a target video generation model to perform video generation processing on the target text to obtain a target video, wherein the target video generation model is a model obtained by performing model alignment on an initial video generation model and a preset reward model in a fine-tuning manner (S22). The present invention solves the technical problems in the related art that a video generated by a video generation model obtained by training based on network data has poor quality and does not meet user expectations.

The invention discloses a vehicle control method, a server and a computer readable storage medium. The method comprises the steps that current perception information is acquired, the current perception information comprises user perception information and vehicle perception information, and the user perception information comprises user voice and / or user behaviors; according to the current perception information, determining an intention label, a user intention and candidate function points; and determining a vehicle control instruction according to the intention label, the user intention and the candidate function points. And issuing a vehicle control instruction to the vehicle to complete vehicle control. Thus, by combining the multi-mode current perception information, distinguishing the intention label of the user intention and understanding and reasoning the user intention, the service meeting the user expectation can be actively provided, and the driving experience of the user is improved.

The invention provides a mechanical arm control method based on a visual language model and human feedback. The method comprises the following steps: a) acquiring scene information: acquiring states of a mechanical arm and objects in a scene in real time through a camera; b) generating a control code according to the user instruction: decomposing the user instruction into a plurality of subtasks by utilizing a large language model, and combining and calling a predefined API (Application Program Interface) to generate the control code; c) verifying the generated control code: verifying the code through a visual language model, and judging that the control code completes a user instruction; d) executing the control codes: sequentially executing the control codes according to the sequence of the subtasks, and judging whether the step is successfully executed or not; and e) fault repair and man-machine interaction: feeding back reasons that tasks are not completed according to expectations, and regenerating control codes according to user feedback. According to the invention, the mechanical arm can understand and execute the natural language instruction of the user, and can communicate with the user when an abnormal condition occurs, so that the mechanical arm can complete various tasks in accordance with the expectation of the user.

The invention relates to the technical field of artificial intelligence digital persons, and particularly discloses an interactive digital person generation method and system based on artificial intelligence, and the method comprises the steps: collecting behavior data, voice data and image data of a real person; constructing a model for generating a digital human according to the collected data; a deep learning algorithm is adopted to analyze the model, initial digital human behavior characteristics, voice characteristics and appearance characteristics are generated, the initial digital human behavior characteristics, voice characteristics and appearance characteristics are input into a generative adversarial network (GAN), the behavior logic, voice logic and appearance logic of the digital human are optimized through the iterative training and optimization process of a generator and a discriminator, and the digital human behavior logic, voice logic and appearance logic are obtained. And finally, the interactive digital human with high authenticity is generated, the high authenticity of the digital human in behavior, appearance and sound is ensured, a personalized digital human image conforming to the expectation of the user is created, the user experience is further improved, the digital human image with high authenticity is generated, and the naturalness and interactivity of communication are enhanced.

A language model is used to generate autosuggestions to complete or revise a user's partial search query. An initial partial query is applied to the language model to generate query candidates for completing the search query. The language model may generate the query candidates as additional or alternate tokens for the partial search query. When the user revises the partial query, the previously-generated candidates can be re-used to reduce subsequent processing time for generating additional candidates. The previously-generated candidates are compared with the revised partial query to select which of the candidates to be re-used and expanded for generating additional tokens. Additional tokens can be generated in parallel for the previously-generated candidates or with model values from the previous generation, enabling the tokens to be generated effectively with reduced latency consistent with user expectations for search-related autosuggestions.

The invention discloses a target model interaction method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a reasoning instruction; performing data reasoning based on the reasoning instruction through the target model to obtain reasoning process data and a reasoning result; wherein the reasoning process data comprises a plurality of branch nodes and a plurality of conclusion nodes which are cascaded in a data reasoning process; and displaying the reasoning process data and the reasoning result. Through the mode, the transparency and the interpretability of the reasoning path of the target model can be improved, and the efficiency of generating the model output result meeting the user expectation by the target model is improved.

The invention discloses a generative AI-driven physiological-music following response intelligent emotion regulation system. The system mainly comprises a physiological signal acquisition module, a signal preprocessing module, an emotion real-time decoding module, a music-emotion response calibration module and a music generation and emotion regulation module. On the basis of the generative AI technology, music expectation, a music tension release mode and other music psychology theories are fused, music capable of directionally adjusting the emotional state of the user is generated through real-time accurate decoding of the emotional state of the user through multi-mode physiological signals, the user expectation is gradually established and released at the high point, roller coaster-like emotional changes of the user are caused, and the user experience is improved. And the user can subjectively obtain pleasant and satisfied positive emotions and the like.

Embodiments of the present application provide an operating parameter recommendation method and apparatus, used for in a big data processing scenario, recommending operating parameters for a computing device on the basis of the resource consumption under different operating parameters, without depending on historical data. The method comprises: first, on the basis of information obtained during the processing of historical tasks in a big data system, establishing a first relationship among the corresponding data information, parameters of a computing device processing the tasks, and time required to process the tasks, and a second relationship among the data information, the parameters, and resources of the computing device consumed for processing the tasks; inputting data information of a task to be processed, and the first relationship and the second relationship to a genetic algorithm, and outputting multiple sets of time values and resource values, i.e., modeling the process of the computing device executing data processing tasks, so as to fit the relationship between the time and resource consumption of the computing device and the operating parameters of the computing device; and determining operating parameters on the basis of actual available resources of the computing device or resource consumption that a user desires.

The invention discloses a few-sample action recognition method in an intelligent healthy environment, which comprises the following steps: inputting a support set and a query set containing video samples, extracting representative frames from each video through a frame extraction algorithm, and performing data enhancement on the representative frames; extracting frame set features of the sample by using a feature extraction network; the method comprises the following steps of: calculating in a transformer, and constructing a support sample feature matched with a query sample; according to the similarity between the intra-class sample features, distributing a weight for each sample; constructing a prototype of each class in combination with support sample features and weights thereof; and calculating the distance between each pair of class prototypes and query sample features, taking the class with the minimum distance as a prediction result, and optimizing the model according to the distance loss. In addition, the invention further discloses a few-sample action recognition system in the intelligent healthy environment. According to the method, various information of the sample is fully utilized, so that the generated action recognition result is higher in accuracy and better conforms to the expectation of the user.

The invention provides an information display method and device, electronic equipment, a storage medium and a program product. The method comprises the following steps: displaying a virtual resource panel on a display interface of a virtual space; and in response to the detected preset event of the virtual space, displaying at least one virtual resource associated with the preset event in the virtual resource panel. When the preset event occurs, the virtual resource associated with the preset event is displayed on the virtual resource panel in real time, so that a user can be helped to quickly position a proper virtual resource, the virtual resource presentation process is smoother and more in line with user expectation, and the interactive experience of the user is improved.

The invention relates to an artificial intelligence technology, and discloses a method for carrying out personalized prediction on a user based on a CLLM model, computer equipment and a storage medium, and the method comprises the steps: constructing a multi-dimensional data set according to collected user preference data and situation factor data; training a pre-constructed CLLM model based on the multi-dimensional data set, so that the CLLM model learns the relevance between the user preference data and the situation factor data, and has the capability of performing personalized output of a natural language based on the relevance; and utilizing the trained CLLM model to perform data analysis on the situation factor data related to the behavior of the target user, and predicting and generating a personalized result meeting the preference of the target user. The invention further discloses a control device. The invention aims to realize that the CLLM model accurately captures the user demand and improve the accuracy of personalized prediction of the user, so that the content output conforming to the user expectation is obtained through prediction.

The invention provides a presentation document generation method and device and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: comparing active input information of a user with a preset theme in a local database, and determining a user expected theme for generating a presentation document; obtaining preset sub-themes under the user expected theme in the local database, generating a user question according to the sub-themes, and determining a plurality of user expected sub-themes for generating the presentation document through conversation between the user question and the user; generating a main title and a plurality of sub titles of the presentation document according to the user expected theme and the plurality of user expected sub-themes; obtaining content data corresponding to each user expected sub-topic in a local database, generating sub-contents of each sub-title according to the corresponding content data, and generating main contents of the main title according to all the sub-contents; the main title and the main content and the sub-title and the sub-content are combined to generate a presentation document. According to the method, comprehensive and professional demonstration documents are generated in combination with database multi-level classification.

The invention discloses a big language model dialogue optimization method, device and equipment and a computer storage medium, and the method comprises the steps: responding to the entering of a current dialogue round, and obtaining configuration information corresponding to the current dialogue round based on the type of the current dialogue round; obtaining user input information corresponding to the current dialogue round; on the basis of a dialogue round switching judgment strategy corresponding to the dialogue round switching strategy configuration information, whether the current dialogue round needs to be switched or not is judged; if switching is needed, determining a next dialogue round corresponding to the current dialogue round based on a dialogue round switching strategy corresponding to the dialogue round switching strategy configuration information, and entering the next dialogue round; if switching is not needed, a reply task is generated based on a reply prompt word corresponding to the reply strategy configuration information and the user input information, the reply task is executed through a large language model, and reply information is generated; reply information is output in the current dialogue round, and user expectation is met.

The invention relates to the technical field of artificial intelligence, in particular to a verbal skill confrontation training generation method and device based on a large model, equipment and a storage medium, and the method comprises the steps: generating a simulation inquiry based on a preset user portrait, then obtaining a response of a service large model, and comprehensively evaluating the response quality; and the specific defect type of the service model in logic understanding or verbal skill expression is diagnosed through the cognitive deviation between the response and the user expectation by another evaluation model, so that a targeted optimization strategy is generated, the service model is finally driven to carry out directional reinforcement learning, and the verbal skill ability of the large service model is iteratively improved. According to the method, an adversarial sample is dynamically generated, and deep diagnosis is carried out in combination with cognitive deviation, so that a service model can understand deep intentions and emotion demands of different user groups fundamentally. Therefore, the strain capacity and the communication accuracy of the service model in a real interaction scene are remarkably improved, and the user satisfaction is effectively improved.

The embodiment of the invention provides an interaction method and device, equipment, a storage medium and a program product. The method includes, in response to receiving a user input, generating a first text based on the user input. And obtaining first rich media content corresponding to at least one part of the first text at least based on the first text. The first text and the first rich media content are presented as at least part of a reply to the user input. In this way, the rich media content corresponding to the reply content can be added based on the reply content to respond to the user input, so that the expected rich media content can be provided as far as possible when the user expects to respond to the rich media content, and the user experience and satisfaction are improved.

The invention discloses a product engineering change execution management method based on a PLM system, relates to the technical field of product management, and has the functions of acquiring changed data through a datamation technology, a development management system and an automatic series PLM system, automatically establishing tasks according to engineering, automatically providing an SOP operation instruction change application form, automatically managing overdue and the like. Platform-based, transparent and intelligent management is realized; the automatic series PLM system obtains the changed data, performs automatic modeling on the changed data, performs automatic conversion and transmission on the changed data, automatically generates task decision arrangements in different environments based on the association rule base, effectively conforms to user expectations, and improves the user experience. Trouble steps, labor cost and time delay of manually transferring the changed data are greatly reduced, efficient feature extraction is performed on the changed data, the relation between the changed data and original data is deeply sensed, generated task decision arrangement has higher robustness, and environment, cost, resources and user requirements are met in multiple aspects.

The invention provides a method and device for making a diversified analysis chart based on a UE engine, and belongs to the technical field of charts.According to the embodiment of the invention, based on source data, a service index weight matrix conforming to a service scene can be obtained, and based on the source data and demand description information, the diversified analysis chart is made. The method comprises the following steps: obtaining a chart type weight matrix which accords with data characteristics and user expectations through a business index weight matrix and a business index weight matrix, further recommending an appropriate chart type to a user while realizing deep analysis of data by comprehensively considering the business index weight matrix and the chart type weight matrix, and further improving the user experience by converting a multi-dimensional matrix into executable parameters of a UE engine. According to the embodiment of the invention, the powerful computing power support of the cloud server and the powerful graphic rendering capability of the UE engine can be utilized to provide a more visual and comprehensive diversified analysis chart for the user, so that the display efficiency is improved, and the use experience of the user is remarkably improved.

The invention discloses a trajectory planning method and device, electronic equipment and a storage medium, and relates to the computer technology, and the method comprises the steps: determining a target region according to obtained region information, and carrying out the feature extraction of map data corresponding to the target region, and obtaining region map features; performing feature extraction on the received image information to obtain required track features; and performing feature matching according to the regional map features and the demand track features to obtain a planned track of the demand path. According to the method and the device, the pattern expected by the user is combined with the real geographical environment in a mode of performing feature matching on the regional map features and the demand track features, an accurate and feasible planning track can be generated according to conditions such as actual roads and terrains, the track planning efficiency is improved, and the user experience is improved. And the beneficial effect of improving the precision and the aesthetic degree of the planned trajectory and the pattern required by the user is further achieved.

The invention discloses an intelligent measurement and control device and an industrial design application method, and the key points of the technical scheme are that the method comprises the construction and application of an AIGC agile industrial design model, a man-machine collaborative design process, the construction of an application normal form of an industrial product generation scene, a model optimization decision based on cognitive analysis, and the research and verification of an application case. According to the AIGC model, the design efficiency and innovativeness are remarkably improved by rapidly generating and optimizing a design scheme; through accurate demand analysis and optimization decision, it is ensured that the design scheme is highly consistent with user expectation, and the user satisfaction degree is improved; an agile design method and multiple iterative optimization ensure that the design process is efficient and accurate, and the design quality and reliability are improved; a design scheme is rapidly generated and optimized, the product development period is effectively shortened, and the market response speed and competitiveness of enterprises are improved.

The invention provides a model updating method, device and system, in the model updating method, computer equipment displays a first processing result obtained by processing system data of a network system according to a model, and a user can perform knowledge data input operation after seeing the first processing result. The computer device obtains target knowledge data obtained after format conversion is conducted on the knowledge data, then the computer device responds to the model updating instruction, a model is updated through the target knowledge data, an updated model is obtained, and finally system data of the network system is processed according to the updated model to obtain a second processing result. And displaying the second processing result. The user can directly participate in the model adjusting and optimizing process, and the model of the user can be updated in real time to meet changing business requirements and personalized expectation of the user.

Described is a method for instilling the haptic dimension of texture to virtual and holographic objects using mid-air ultrasonic technology. A set of features is extracted from imported images using their associated displacement maps. Textural qualities such as the micro and macro roughness are then computed and fed to a haptic mapping function together with information about the dynamic motion of the user's hands during holographic touch. Mid-air haptic textures are then synthesized and projected onto the user's bare hands. Further, mid-air haptic technology enables tactile exploration of virtual objects in digital environments. When a user's prior and current expectations and rendered tactile texture differ, user immersion can break. A study aims at mitigating this by integrating user expectations into the rendering algorithm of mid-air haptic textures and establishes a relationship between visual and mid-air haptic roughness.

The embodiment of the invention provides an alarm information processing method, device and system, and an alarm information auxiliary processing method, device and system, and the method can comprise the steps: receiving first alarm information reported by a first camera device, and the first alarm information comprises a first alarm video; performing multi-modal feature extraction on the first alarm video to generate a first multi-modal feature vector; and based on the first multi-modal feature vector and a decision matching object, generating a push decision of the first alarm information, the decision matching object being determined according to a labeled visual sample uploaded by the client, and the labeled visual sample being obtained by labeling a visual sample by a user at the client. In this way, more accurate alarm content which better conforms to the expectation of the user can be provided.

The invention discloses a space computing power network task migration method and system based on dynamic environment perception, and relates to spaceflight electronics and data processing technologies, and the method comprises the steps: determining that a user node obtains a computing resource needed by a computing power service from a satellite node in a space computing power network; calculating a task migration moment caused by satellite node movement and an alternative satellite set capable of receiving tasks according to the dynamic environment information; based on a candidate satellite set, an optimal satellite is screened out according to different user expected targets, before the migration moment arrives, a calculation task is migrated to the selected satellite in advance, and seamless continuity of services is guaranteed; and for the high-priority task, carrying out redundancy migration on the alternative scheme without computing resource intersection. According to the method, the problems of low efficiency, service interruption caused by sudden faults, multi-target optimization conflicts, resource shortage scene migration failure and the like of a traditional migration algorithm in a spatial network topology dynamic scene can be effectively solved.

The invention relates to the technical field of shoe product customization, in particular to a shoe product management system for big data processing shoe material customization, which comprises a data collection and preprocessing unit, a natural language processing core unit, a quantitative index generation unit and a customization process fusion unit, a data collection and preprocessing unit collects and standardizes expected text data of a user for shoe materials, a natural language processing core unit identifies user intentions, keywords and modifiers and analyzes demand priorities, a quantitative index generation unit converts functional demands and style preferences into quantitative indexes and feature vectors, and the quantitative indexes and the feature vectors are stored in a database. The customization process fusion unit inputs quantitative indexes into a computer aided design model, screens shoe materials, adjusts design parameters and generates a design scheme, defines a design direction by using a quantification means, reduces errors between user expectations and design results, considers shoe material cost and supply conditions, meets diversified requirements of users, and improves design efficiency. And the shoe product customization quality and the user satisfaction are improved.

The invention provides a freight screening result display method and a computer readable storage medium, and terminal equipment receives freight search information input by a user on a freight search interface, and sends a freight search request carrying the freight search information to a server after receiving a search operation on the freight search interface. The server responds to the freight search request and performs recall operation on all the current transportation demand lists according to the freight search information and information of a first user corresponding to the terminal equipment to obtain recalled transportation demand lists; and sorting the recalled transportation demand orders based on the degree information that each recalled transportation demand order accords with the expectation of the first user and the generalization degree information of each recalled transportation demand order to obtain a screening result. And the server sends the screening result to the terminal equipment, and the terminal equipment displays the screening result. Therefore, the order receiving efficiency of the driver is improved, the order reaching efficiency of the cargo owner and the driver is improved, and the user experience is improved.

The invention provides a scheme recommendation method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of computers. The method comprises the following steps: acquiring target information; the target information is used for indicating at least one service demand satisfied by a target space expected by a target user; performing intelligent analysis based on the target information and the intelligent device in the target space to obtain an intelligent analysis result; based on the intelligent analysis result, determining a target device which needs to be configured and meets the service demand, and generating a corresponding intelligent recommendation scheme; the intelligent recommendation scheme is used for recommending the target equipment which needs to be configured and meets the service requirement to the target user. The problem that it is difficult for a user to select a proper intelligent device in the prior art is solved.

The invention relates to the technical field of advertisement design, and discloses an AI virtual human interaction method and system, and the method comprises the steps: receiving original demand data inputted by a user, generating a brand feature vector, and generating first virtual human data, first line data and first product model data based on the brand feature vector; and performing cooperative adjustment based on the ith interaction instruction to generate a virtual human image. By implementing the method and the system, the functions of full-process intelligent design, data processing, collaborative generation, interactive response, scene adaptation and the like are improved, an efficient and complete virtual human image customization scheme is formed, and the problem that multi-source heterogeneous data are difficult to comprehensively analyze when user requirements are processed by a traditional method is solved. The problems of large deviation between generated content and user expectation and poor scene adaptability caused by lack of a collaborative adjustment mechanism of a virtual human image, lines and a product model, low processing efficiency of a modification instruction and incapability of ensuring cross-modal consistency in the prior art are solved.

The invention relates to the technical field of AI, and discloses an intelligent image processing method and system based on AI.The method comprises the following steps that a user provides input data, and the input data comprise an original picture, text description and multi-modal information; using a pre-trained target detection algorithm to process object recognition in all original pictures in batches; classifying the objects identified in each picture, and marking the categories of the objects; extracting a group of standardized features of each class of objects; and for each object in each picture, according to the standardized features of the object and the keyword matching degree in the user text description. According to the method, the intention and preference of the user are accurately understood by introducing the multi-modal information and performing feature extraction on the original picture provided by the user, and important objects can be preferentially considered in the generation process based on a comprehensive scoring system of feature similarity, keyword matching degree and multi-modal influence; and the generated result better accords with user expectation.