6results about How to "Personalized service" patented technology

The invention discloses an item type self-growth and self-evolution and classification method based on a large model. The method comprises the steps that item type catalogs are added to a large language model, and corresponding item classification cues are constructed; inputting the government affair hotline work order text and the item classification prompt word into the fine-tuned large language model, and quoting an item type directory to output an item type corresponding to the government affair hotline work order text; and outputting the item type output by the large language model as a classification result of the to-be-classified government affair hotline work order text. The item type catalog needs to be periodically updated based on the large language model. Prediction of government affair hotline item types is achieved in the mode that the large language model is combined with the item classification prompt words, meanwhile, fine adjustment is conducted on the large language model so that the large language model can be more focused on the field of government affair hotlines, and item type self-growth and self-evolution of the item type catalog are achieved through the large language model. Therefore, the timeliness and accuracy of government affair hotline item type prediction are improved.

The invention relates to an intelligent customer service method, and aims to provide personalized and accurate customer service reply through advanced technical means. The method comprises the following steps: firstly, acquiring and analyzing a query request of a user regardless of the form of text, voice or image; thirdly, intention recognition is conducted through a preset response model, a user portrait is generated in combination with historical interaction data of the user, and customer service requirements are predicted according to the user portrait. And by correcting the prediction intention data and considering the user preference, an accurate customer service reply is generated. In addition, the system also collects subsequent behavior data of the user, constructs a service scoring data set, and continuously optimizes the service model by using a machine self-learning algorithm. According to the method, the user satisfaction can be effectively improved, the click rate and the conversion rate are increased, the response time is shortened, the problem solving rate is improved, and continuous service optimization and performance improvement are realized.

This invention discloses a precise legal consultation method and system based on multi-agent orchestration. The method includes: employing a hybrid intent classification mechanism with three levels of linkage—LLM remote reasoning, local heuristic correction, and keyword fallback—to route user requests to different paths, driving differentiated processing flows; performing dual-path retrieval of vector retrieval and knowledge graph relationship expansion in deep analysis to generate a structured analysis report; introducing a multi-dimensional context compression algorithm to reduce token overhead and illusion risk; embedding a three-stage emotional reassurance mechanism throughout the entire response process; and using a rendering type protocol to achieve front-end / back-end decoupling and unified rendering across multiple platforms, decomposing the processing into continuous dynamic feedback through a staged streaming response mechanism. This invention achieves intelligent, precise, and emotionally engaging legal consultation processes through multi-agent orchestration, significantly reducing model reasoning costs and improving the handling capacity for complex cases and user interaction experience.

The invention relates to the technical field of data exchange, in particular to a virtual digital human interaction management method and system based on artificial intelligence. Comprising the following steps: S1, establishing a portrait identity database, and independently storing a consultation record of each user according to portrait data; s2, collecting historical business consultation data of a bank, and then carrying out statistical analysis on the historical business consultation data by utilizing artificial intelligence so as to obtain the number of first consultation times of each business type; through different processing modes for new users and old users, services can be provided for the users more efficiently, input voices of the new users are analyzed in combination with historical consultation service data, service matching is performed in combination with the number of times of first consultation, accurate information of related services can be provided for the new users quickly, and user experience is improved. And the old user can carry out business matching according to the historical consultation record in the association effective time threshold value and the business type associated with the consultation sequence, so that more personalized services are provided.

The utility model belongs to the technical field of government affair processing, and particularly relates to a government affair service self-service terminal all-in-one machine which comprises a touch display screen movably connected to the top end of a shell, a face recognition camera movably connected to the top end of the touch display screen, an electromagnetic sign pen fixedly installed on one side of the outer surface of the shell, and a display screen movably connected to the other side of the shell. An electromagnetic signature board is installed at the top end of the shell in an embedded mode, a fingerprint touch module is installed at the position, located on one side of the electromagnetic signature board, of the top end of the shell in an embedded mode, and a two-dimensional code scanning module is installed on the inclined face, relative to the ground, of the shell in an embedded mode. The identity recognition difficulty is reduced, the applicability and the service efficiency are improved through multiple modes, the information safety is guaranteed through identity recognition, meanwhile, user operation is facilitated, the service quality can be improved, the requirements of the user can be better known, and more personalized services are provided for the user.

The invention relates to the technical field of natural language processing, in particular to a cultural relic explanation method applied to natural language processing NLP and artificial intelligence and based on multi-modal user intention recognition and alignment. The method comprises the following steps: firstly, receiving various inputs provided by a user through a multi-modal alignment module, such as voice, characters, pictures, geographic positions and the like, and outputting two values, namely a final dialogue and an object main body; then, when the object main body exists, the content and the main body noun are combined and optimized into a prompt dialogue through a prompt project, and the prompt dialogue is used as input of an intention recognition model; thirdly, performing intention recognition on the prompt dialogue by using an intention recognition model, and performing intention division according to a recognition result; meanwhile, a large amount of data related to cultural relics are collected, the data are cleaned, preprocessed, labeled and classified, the labeled data are used for model training, and parameters are adjusted to achieve the optimal intention classification and named subject recognition effects. And providing services for the user by combining contents of intention recognition and named subject recognition.