9 results about "Product source" patented technology

The invention provides a personalized recommendation method and system based on a knowledge graph, and relates to the technical field of knowledge graphs. The method comprises the following steps: firstly, collecting multi-source heterogeneous data such as basic information of a product source, a delivery period of a product, financial constraints, policy constraints and user behaviors, and writing the multi-source heterogeneous data into a shopping knowledge graph through intelligent cleaning and entity-relationship extraction; then, combining user budget, preference and purchase qualification to construct a user portrait, and reasoning and screening a compliance product source candidate set in the knowledge graph by taking the portrait as a retrieval condition; generating a comprehensive score for each product source in the candidate set according to the preference matching degree, the price adaptation degree, the matching integrity and the appreciation potential, and sorting the score; and finally, a plurality of product sources with the highest comprehensive score and corresponding three-section recommendation explanations are output, deep fusion of multi-source data is achieved, and it is ensured that the recommendation result is accurate, compliant and interpretable.

The present application relates to a kind of based on point source list and big product source flow direction modeling method of big product source, belong to traffic and environmental management technical field.It includes: constructing big cargo source database, using 5G positioning and big dipper trajectory data, by time-space fusion algorithm cleaning and reconstruction trajectory, identify key transport stop point;Dynamic spatial matching model is built to optimize correlation strategy, based on graph neural network integrates production plan and demand forecast generates potential path, through double-dimensional evaluation system planning candidate route;Adopt block chain technology to collect multi-source heterogeneous data, through intelligent prediction model realizes path classification and scheme formulation, and utilize adversarial generative network and expert knowledge graph to verify and update rule;Based on digital twinning technology realizes the dynamic mapping of transport path, through time-space big data analysis and causal inference model mining logistics correlation and forecast optimization direction.The accurate modeling and decision support of source-flow-direction relationship are realized.

The invention relates to a bulk product source flow direction modeling method based on a point source list and a Beidou track, and belongs to the technical field of traffic transportation and environment management. The method comprises the steps that a bulk goods source place database is constructed, 5G positioning and Beidou trajectory data are utilized, reconstructed trajectories are cleaned through a space-time fusion algorithm, and key transportation staying points are identified; constructing a dynamic space matching model optimization association strategy, integrating a production plan and demand prediction based on a graph neural network to generate a potential path, and planning a candidate path through a two-dimensional evaluation system; a block chain technology is adopted to collect multi-source heterogeneous data, path classification and scheme making are realized through an intelligent prediction model, and a generative adversarial network and an expert knowledge graph are utilized to verify and update rules; dynamic mapping of a transportation path is realized based on a digital twinning technology, and logistics association is mined and an optimization direction is predicted through space-time big data analysis and a causal inference model. And accurate modeling and decision support of the source-flow-direction relationship are realized.

This invention relates to the field of logistics technology, specifically to a traceability management method and system for industrial products. The method includes the following steps: reading operation count values ​​and timestamp values; matching segment numbers according to a segment interval table; reading batch codes and product serial numbers; combining node numbers with entry and exit times; comparing the number order to supplement information; and associating segments with product codes to obtain product traceability information. In this invention, by reading equipment operation count values ​​and matching them with timestamps and operation segment interval tables to generate equipment operation segment information, and combining this information with the production line equipment number sequence to write into the product identifier, the ability to present production status and sequence is improved. In the logistics flow, by comparing the entry and exit time sequences and establishing a continuous relationship by combining scan numbers with preceding numbers, and associating node sequences with equipment operation segments and product codes, a continuous link between production stages and logistics flow is constructed, reducing the impact of mis-ordered records on product origin determination.

This invention discloses a user targeting method based on big data analysis, belonging to the field of user targeting technology. It addresses the problems of reduced shopping cart conversion efficiency and increased resource waste in recommendation systems. By setting an analysis time, the method monitors the frequency of user visits to the shopping cart to determine whether the user enters the product analysis mechanism. When the product analysis mechanism is entered, the method statistically analyzes the access interval of various products, extracts the user's conversion cycle benchmark from the historical database, calculates the interaction decay characteristics based on the access interval, and analyzes the cooling-off ratio to determine whether the user is in the interest cooling-off stage. For the interest cooling-off stage, the method extracts the product dwell time and product source information, calculates the channel stickiness index of different product source channels, and comprehensively calculates the scheduling priority score by combining the channel stickiness index and product dwell time. This adjusts the display order of products in the shopping cart, increasing the display weight of high-potential products and improving shopping cart conversion efficiency and recommendation accuracy.

The utility model discloses an anti-fake traceability interlink cap, which belongs to the technical field of bottle caps, and is characterized by comprising an outer cap body and an inner cap body, the inner cap body is arranged inside the outer cap body, the outer cap body is rotatably connected with the inner cap body, the inner cap body is matched with a bottle opening, and the inner cap body is connected with the inner cap body. A connecting bridge is arranged between the opposite sides of the outer cap body and the inner cap body, a weak notch is formed in the connecting bridge, a sealing gasket is arranged in the inner cap body, and the anti-fake traceability of the bottle cap is improved from multiple dimensions by arranging the anti-fake traceability mark which is of a multi-layer composite structure; a unique biological identity card can be endowed to the product and is difficult to copy; and the complexity and the uniqueness of visual anti-counterfeiting are increased, so that consumers can quickly and conveniently verify the authenticity of the product and trace the source of the product, the difficulty and the cost of counterfeiting are greatly improved from the technical level, and a powerful anti-counterfeiting traceability guarantee is provided for the product.

A method of product detection includes receiving, at a product detector from a product source, a first annotation package for a first product and a second annotation package for a second product. An artificial intelligence model is trained to detect the first product based on the first annotation package and the second product based on the second annotation package. The artificial intelligence model is implemented on the product detector. At the product detector, the first product is categorized into a first category of products and the second product is categorized into a second category of products. A subscription is received from a retailer to one of: the first category of products; the second category of products; and the first category and the second category of products. An image is received at the product detector from the retailer. The first product is detected in the image by the artificial intelligence model.

The application discloses a kind of digital warehouse management method and system, it is related to warehouse management technical field, including: obtaining receiving batch product warehousing information, extraction product transport area information and product source area information;Based on relational database to build storage architecture, according to product transport area information to generate first segment code, according to product source area information through encryption algorithm to generate the second segment code of product;Through CRC-32 cyclic redundancy check algorithm to obtain check code, in combination with the first segment code and second segment code to generate product information coding;According to the first segment code of product information coding to allocate the warehouse storage area of product, generate storage management information table, according to the second segment code of product information coding to carry out classification registration to product, generate inventory data information table.Through the construction of double segment coding data model, execute encryption processing and role-based access control, the problem that the existing warehouse system operation efficiency is low, data security risk is high is solved.

The invention discloses a light aging simulation and toxicity detection method for plastic microbeads from wash care products, and belongs to the technical field of cosmetic detection, and the method comprises the following steps: (1) extraction and purification; (2) aging treatment; (3) physical and chemical characterization and free radical detection; and (4) biotoxicity detection. The method provided by the invention provides a set of complete methodological process of extracting the microbeads from the wash care products, simulating light aging, detecting free radicals and evaluating biological toxicity; the system reveals the toxicity risk of the light aging plastic microbeads in the environment, and provides a scientific basis for environmental health risk assessment and product safety supervision; the method is an operable and repeatable standard method, can simulate the aging process of the microbeads in the environment at the same time, and comprehensively evaluates the potential toxicity effect of the microbeads.