3 results about "Search engine technology" patented technology

The invention belongs to the technical field of search engines, and particularly relates to an optimized search engine construction method and system based on feature deep learning, and the system comprises a search operation unit, a monitoring and early warning unit and a management and control terminal, the search operation unit comprises a multi-dimensional semantic feature mining module, a user implicit intention analysis module, a deep feature fusion modeling module and a dynamic retrieval strategy generation module; a multi-dimensional semantic feature set and a user intention feature set are formed through a multi-dimensional semantic feature mining module and a user implicit intention analysis module, and a deep feature fusion modeling module performs deep fusion of data features and user intention features through an attention mechanism and cross validation optimization. The dynamic retrieval strategy generation module is used for providing high-quality feature support for retrieval strategy generation, the accuracy of retrieval results is guaranteed, the dynamic retrieval strategy generation module generates dynamic strategies adaptive to different requirements and data states on the basis of reinforcement learning, and the retrieval accuracy and retrieval efficiency of a search engine are remarkably improved.

The present disclosure provides a page search method, device, equipment and medium, relates to the field of computers, in particular to computer network technology, search engine technology and software application technology. The method comprises the following steps: determining a candidate page based on a query request; determining at least one candidate page area in the candidate page; determining the weight of each of the at least one candidate page area based on a preset rule for the candidate page; calculating the matching degree between the query request and each of the at least one candidate page area; and determining the matching degree between the query request and the candidate page based on at least the matching degree between the query request and each of the at least one candidate page area and the weight of each of the at least one candidate page area.

The invention relates to the technical field of generative search engines, and discloses a generative search engine-oriented content acquisition probability evaluation and structure optimization system. The system comprises a multi-dimensional probability quantitative evaluation module which decomposes answer content into a fact statement unit, calculates source credibility, semantic association degree and multi-source consistency three-dimensional sub-scores in parallel, fuses a generation unit credibility acquisition probability, aggregates an output unit credibility acquisition probability, and identifies a low-confidence evaluation factor; the credibility-driven structured optimization module is used for carrying out semantic segmentation on answer contents according to the unit credit collection probability, carrying out enhanced presentation on high-confidence facts and carrying out risk prompt and evidence association display on low-confidence statements; and the closed-loop feedback optimization module is used for triggering supplementary retrieval according to the evaluation factors, inputting new evidences into re-evaluation and driving the structured optimization module to perform real-time adjustment. According to the method, credibility quantification, structured presentation and retrieval-optimization closed loop are realized, and the credibility and interpretability of the generated answer are improved.