6results about How to "Efficient retrieval" patented technology

The application discloses an enterprise collaborative office method and system based on intelligent AI, and the method comprises the following steps: collecting and preprocessing the data of each end of the enterprise collaborative office; constructing an AI collaborative engine containing multiple AI models, and training and optimizing each model by using the preprocessed data; the AI collaborative engine analyzes the semantics and intention of the input information of each end, automatically triggers the corresponding process and allocates tasks, adjusts the allocation strategy according to the execution situation; automatically identifying the relevant departments and personnel of cooperation, establishing a temporary collaborative team and generating a cooperation report; performing hierarchical permission management on the data of each end, monitoring abnormal behavior and generating a security audit log; combining the task execution and process operation data, continuously iterating and optimizing each model of the AI collaborative engine. The enterprise collaborative office method and system based on intelligent AI solve the problems of existing collaborative office data islands and insufficient intelligence, improve the collaborative efficiency and management level, and adapt to the needs of enterprise digital transformation.

The application relates to the technical field of radar signal sorting, and provides a jitter PRI sequence retrieval method and device based on a full convolution network. The method introduces a PP sequence as a supplementary feature of a DTOA sequence in pulse sequence retrieval, uses a trained jitter PRI sequence retrieval model based on a full convolution network to retrieve the DTOA sequence and the PP sequence, effectively retrieves the jitter PRI sequence without needing an a priori jitter upper bound, and significantly improves sequence retrieval performance.

The application provides a question and answer method and system based on a large language model, which comprises the following steps: determining a current question of a user and a natural language understanding prompt word; inputting the current question and the natural language understanding prompt word into a pre-trained large language model to obtain a question understanding result and a question to be answered output by the large language model according to a natural language understanding strategy; in the case that the question understanding result is a factual question, retrieving an answer from a knowledge graph based on semantic analysis; inputting the retrieved answer and an answer verification prompt word into the pre-trained large language model to obtain an answer verification result; in the case that the verification is reasonable, taking the retrieved answer as the final answer to the current question; and in the case that the verification is unreasonable, generating an answer by the large language model. In the multi-round question and answer task, the application can deeply understand the question of the user based on the context, effectively retrieve and integrate information from different knowledge sources, and thus accurately and efficiently provide an answer to the current question.

The application provides an intelligent power data retrieval system, which comprises a data acquisition module, a data processing module, a retrieval interaction module, an intelligent matching module, a retrieval output module and a retrieval security module; the data acquisition module is used for acquiring real-time and historical multi-source power data and storing the multi-source power data in a power database; the data processing module is used for performing a preprocessing operation on the acquired multi-source power data and extracting power data features; the retrieval interaction module is used for receiving retrieval request information of a user and analyzing the retrieval request information; the intelligent matching module is used for performing similarity matching between the analyzed retrieval request and the power data features; the retrieval output module is used for feeding back the matching result of the intelligent matching module to the user in a preset format; and the retrieval security module is used for guaranteeing the safety of the multi-source power data in the acquisition, transmission, storage and retrieval processes. The application can realize efficient retrieval of power data and improve retrieval accuracy and response speed.

This invention relates to the field of information retrieval and data visualization technology, and discloses a visual text search method based on a hybrid data model. The method includes: constructing a hypergraph hybrid model by associating a graph database and a vector database using global identifiers; identifying the intent of user queries; generating structured search instructions for the graph database and semantic similarity search instructions for the vector database; fusing and expanding the two types of search results based on global identifiers to form a search result set containing an extended knowledge graph, a list of semantic vectors, and traceable links between them; and finally, converting the result set into a dynamic and interactive visual view according to predefined mapping rules and a hybrid mechanics layout algorithm. This invention effectively unifies semantic retrieval and relational retrieval, improves the comprehensiveness and accuracy of retrieval, and significantly enhances the depth of information understanding and user experience through intelligent visualization and interaction mechanisms.