5 results about "Product innovation" patented technology

The application provides a metadata analysis processing method and device, and relates to the technical field of big data analysis processing.The method comprises the following steps: collecting metadata in a data source; acquiring a business process, declaring the granularity of a metadata model according to the business process, and constructing a dimension table and a fact table according to the granularity; taking the business process as a modeling driver, and establishing a metadata model according to the metadata, the dimension table and the fact table; when a data analysis request is acquired, performing data analysis by using the metadata model to obtain an analysis result.The metadata model is established by collecting metadata, the metadata of enterprises scattered in multiple application systems is centrally managed, a complete and comprehensive data structure relationship is presented for the enterprises, the enterprises are assisted in centrally and efficiently managing data assets, the metadata analysis processing of different business requirements can be met, data value can be mined from the analysis result to guide business or product innovation, and the production of enterprises is empowered.

The application provides an enterprise full life cycle credit risk decision method and system based on multi-source data, the system gathers multi-source heterogeneous data such as industry and finance, and breaks the information island; the system extracts the characteristics of nine dimensions such as enterprise basic information and operation behavior, constructs super web variable, traces back the history growth context of the enterprise, and identifies the dynamic risk characteristics of the enterprise in different life cycle stages; the system supports self-service training of quantitative models, and can be applied to product innovation, risk decision and post-loan management and other credit whole processes. The application realizes the dynamic risk identification and self-service decision of the credit whole process by deeply fusing multi-source heterogeneous data to construct the enterprise full life cycle credit portrait, and effectively helps financial institutions to break the data island and realize digital transformation.

The invention relates to the technical field of data processing of financial and medical scenes, and discloses an insurance product data processing method and device, computer equipment and a storage medium, and the method comprises the steps: accessing multi-source heterogeneous data, and processing the multi-source heterogeneous data into standardized structured data resources and unstructured data resources; calling a plurality of agents to process the structured data resources and the unstructured data resources to generate a plurality of items of intermediate data related to the insurance product; and receiving the multiple items of intermediate data, performing comprehensive optimization on the multiple items of intermediate data by using a multi-objective optimization algorithm, and generating and outputting an optimal insurance product data packet. According to the invention, a complete intelligent product research and development closed loop is constructed, and full-process coverage from data acquisition to product output is realized through multi-agent division cooperation; the product innovation efficiency is remarkably improved, the research and development period is greatly shortened, and meanwhile the market precision and compliance reliability of products are effectively improved through data-driven intelligent analysis.

This invention discloses a product design method, apparatus, and computer storage medium, relating to the field of product design technology. The invention includes product design data acquisition, knowledge preprocessing, multi-source heterogeneous knowledge fusion, and product design optimization decision-making. By integrating objectively existing demand, resource cost, time cost, information flow, and design process structure data, a multi-objective optimization model is constructed with function, cost, and evolutionary trends as its core. Design constraints are introduced to establish an optimization model that maximizes process value. Multiple evolutionary algorithms are used to solve for the optimal structural parameters and resource allocation strategies. Decision-making indicator data are analyzed from the entire design stage. This provides intellectual support for designers to expand innovative thinking, significantly shorten the R&D cycle, and enhance product innovation and competitiveness.