7results about How to "Improve user satisfaction" patented technology

The invention discloses an intelligent costume design recommendation system based on big data, which belongs to the technical field of intelligent costume design and comprises a data acquisition and processing module, a portrait construction module, an intelligent costume design module and a recommendation scheme generation module. According to the method, the multi-modal fusion and dynamic style anchor point combined user scene portrait construction method is adopted, so that comprehensive integration of user body types, long-term and short-term style preferences and scene wearing and building requirements is realized, and a recommendation system can capture current interests and popular trends of the users in real time; generating a personalized costume design conforming to the aesthetic appreciation of the user and adapting to an actual scene; intelligent costume design is carried out by combining conditional potential diffusion costume generation and aesthetic wearable joint evaluation, a design drawing considering the body type, style preference and use scene of a user at the same time is generated, and visual aesthetics and actual wearing feasibility double evaluation is carried out on a generation result, so that it is ensured that recommended costume design meets aesthetic requirements, and the user experience is improved. And the garment is comfortable and fit in real wearing.

The invention discloses a personalized doll clothing customization system based on traditional clothing elements, and relates to the technical field of clothing customization. Comprising a traditional costume element library module which is used for constructing a database in a layered manner according to a shape type, a pattern type and a color type and storing traditional costume elements, and each traditional costume element is attached with core feature parameters marked by AI, and is used for quickly retrieving and calling the traditional costume elements. According to the method, traditional clothing element feature parameters are accurately collected and labeled through the traditional clothing element library module, traditional clothing element features and customized keywords in user requirements are extracted in combination with the multi-modal input analysis module, and then the AI adaptation optimization module uses a proportion adjustment algorithm and a density adjustment algorithm; therefore, the traditional clothing elements are precisely matched with the size of the doll clothing, core details such as pattern texture and shape and structure are kept, and the problem that the traditional clothing elements are distorted to be matched with the small-size model of the doll clothing is effectively solved.

This invention discloses a charging and swapping user behavior pattern analysis system and method, relating to the field of electric vehicle charging management technology. It acquires and establishes a multi-source data pool, merges the multi-source data pool, analyzes user charging and swapping behavior patterns and calculates the probability of abnormal behavior, establishes dynamic scheduling rules based on user charging and swapping behavior patterns, performs resource allocation and service classification, optimizes the model and establishes a response mechanism, and generates real-time scheduling instructions. This invention, through multi-source data collection and analysis, accurately predicts user charging and swapping behavior, dynamically optimizes resource allocation, improves charging station operating efficiency and user satisfaction, promotes the integration of virtual power plants, constructs a vehicle-to-grid strategy optimization module, quantifies the potential of users to participate in grid peak shaving, and optimizes regional energy dispatch. Furthermore, it has an anomaly detection and response mechanism to ensure safety and stability, and promotes the development of charging and swapping services towards high efficiency, intelligence, and sustainability.

The invention relates to a parking management method and device, computer equipment, a storage medium and a product, and relates to the technical field of traffic. The method comprises the steps of obtaining parking characteristic parameters of a target vehicle; the parking characteristic parameters comprise a destination, vehicle attribute data and parking habit data; the parking habit data is used for representing parking preferences or historical parking behaviors of a vehicle driver; based on the parking characteristic parameters, generating parking space constraint conditions matched with the target vehicle; in a target range determined based on the destination, carrying out idle parking space query based on the parking space constraint condition to obtain a target idle parking space; generating a recommended parking strategy for the target vehicle based on the target idle parking space; according to the invention, fine-grained parking space suitability accurate matching can be realized, the parking space recommendation accuracy and individuation level are improved, and the practicability of the recommendation result and the user satisfaction in a complex actual parking scene are improved.

The invention discloses a digital human interaction strategy optimization method based on big data recognition, and relates to the technical field of intelligent interaction and digital human, and the method comprises the steps: collecting and storing multi-modal interaction data, such as texts, voices, expressions and time lengths, generated in a digital human interaction process of a user; performing emotional state labeling on the multi-modal interaction data based on a pre-trained emotion recognition model, and extracting an emotional feature vector containing emotional polarity, emotional intensity and emotional stability; constructing a user emotion change track map to recognize an emotion state conversion mode; evaluating and sorting candidate interaction strategies according to the conversion mode in combination with historical interaction data, and selecting an optimized interaction strategy; and the strategy evaluation index is updated according to user feedback, so that the adaptive optimization of the digital human interaction strategy is realized.

The embodiment of the invention provides an air ticket recommendation method based on an air ticket secondary card and a computer program, and the method comprises the steps: obtaining an air ticket search request of a user using the air ticket secondary card, and the air ticket secondary card is provided with a corresponding application range, is used for the user to exchange an air ticket in the application range, and has the use frequency; wherein the application range at least comprises an air ticket exchange range, and the air ticket search request at least indicates a user travel place; based on the air ticket search request, reservable air ticket results are recommended to the user, the reservable air ticket results comprise extended reservable air tickets which are adaptive to the travel place of the user and exceed the air ticket exchange range, and the extended reservable air tickets at least support the user to use the air ticket secondary card for exchange. And supplementing the original reservable airline ticket in the application range. According to the embodiment of the invention, the user use success rate of the air ticket secondary card can be improved, and the user satisfaction is improved.

This application relates to the field of data processing technology, and provides an information push method, apparatus, and device to solve the problem that the information pushed to users by the banking system cannot meet the personalized needs of users. First, multi-source data of the target user is acquired, and the multi-source data is processed to obtain user profile tags for the target user. Then, a large language model is used to perform semantic analysis on the user profile tags to obtain the user profile analysis results for the target user. Furthermore, a content generation model is used to process the user profile analysis results to generate the information to be pushed to the target user. Finally, the information to be pushed is sent to the target user through the target information push channel. This application's embodiments, by deeply constructing user profiles, comprehensively understand user needs and preferences, enabling banks to provide tailored push content for each user, significantly improving service targeting and user satisfaction.