47 results about "Product base" patented technology

Methods, computer systems, and computer-storage media are provided for efficiently generating product profile recommendations, among other things. In embodiments, catalog content and customer content associated with a product type of a product is obtained. Thereafter, candidate attributes for the product are identified from the catalog and customer content associated with the product type. A model prompt is generated to be input into a large language model. The model prompt includes the candidate attributes, or a portion thereof, a product profile associated with the product, and an instruction to generate a recommendation for a new attribute to associate with the product based on the product profile and the candidate attributes. An attribute recommendation is generated, via the large language model, that recommends the new attribute to include in the product profile. Such an attribute recommendation is provided as a recommendation to include in the product profile associated with the product.

Methods and apparatus are disclosed regarding an e-commerce system that promotes sales of products based on product comparisons. Some embodiments may present a marketing message that justifies a price difference between presented products based on attribute differences between the presented products.

The invention discloses a stacking-based steel hot-rolled product mechanical property prediction method, and relates to the technical field of steel product quality prediction. The method comprises the following steps: constructing a steel hot rolling actual production data set and carrying out missing value interpolation on the data set; performing normalization processing on the complete data set, and dividing a part of data from the normalized data set as a training set; establishing a stacking ensemble learning model based on a regression chain; taking the yield strength, the tensile strength and the elongation in the training set as training labels, taking other data types as training features, and training the learning model by using the training set to obtain a steel hot-rolled product mechanical property prediction model; and the steel hot-rolled product mechanical property prediction model is practically applied to perform real-time prediction on the mechanical property of the steel hot-rolled product. According to the method, the coupling relation among the multiple target variables can be effectively processed, and the accuracy and stability of mechanical property prediction of the steel hot-rolled product can be effectively improved.

To provide a commodity sales data processing system allowing a customer to register a commodity by using a terminal device, in which the customer can properly perform a procedure for cancelling registration of the commodity.SOLUTION: A commodity sales data processing system allowing a customer to register a commodity by using a terminal device, includes: detection means for detecting cancellation of the commodity from a commodity input unit into which the commodity secured by the customer is input; and notification means for providing the customer with notification related to cancellation of registration of the registered commodity on the basis of the detection result by the detection means.SELECTED DRAWING: Figure 14

This utility model discloses an automatic centering and tensioning clamp and a product processing system, relating to the field of clamping technology. The automatic centering and tensioning clamp includes a fixed base with an adjusting plate hinged to it. A first driving assembly is mounted on the adjusting plate, and the power output end of the first driving assembly is connected to an adapter. A product base is mounted on one side of the adapter, and a positioning post is mounted on the product base. The positioning post has a first mounting hole and a second mounting hole. A driving component is located in the first mounting hole, and a positioning block is located in the second mounting hole. A second driving assembly is located between the adapter and the product base. The power output end of the second driving assembly drives the driving component, which in turn drives the positioning block. After extending out of the second mounting hole, the positioning block can tension and fix the product sleeved on the positioning post. This utility model can solve the problem of ineffective positioning and clamping of ring-shaped / tube-shaped products.

To automatically identify a sequence of recommended account / product pairs with highest likelihood of becoming a realized opportunity, an account / product sequence recommender uses an account propensity (AP) model and a reinforcement learning (RL) model and target engagement sequence generators trained on historical time series data, firmographic data, and product data. The trained AP model assigns propensity values to each product corresponding to received account characteristics. The trained RL model generates an optimal sequence of products that maximizes the reward over future realized opportunities. The target engagement sequence generators create target engagement sequences corresponding to the optimal sequence of products. The recommender prunes the optimal sequence of products based on the propensity values from the trained AP model, the completeness of these target engagement sequences, and a desired product sequence length. The recommender uses the remaining products, validated on three models, for account / product recommendations.

This application discloses a product code generation method, apparatus, device, and storage medium, relating to the field of data processing technology. The method comprises: obtaining at least one type of product information of a target product; wherein different types of product information are used to represent information under different attributes of the target product; and generating a first product code for the target product based on the at least one type of product information to improve the convenience of product management.

The invention relates to an independent station commodity query method and device, equipment and a medium, and the method comprises the steps: obtaining a commodity query word expressed in a non-central language, determining whether the commodity query word is a polysemy word or not according to a polysemy word corpus, and calling a central language translation model to translate a plurality of translation words expressed in a central language when the commodity query word is the polysemy word; inputting a commodity query word and a plurality of translation words thereof into a multi-category prediction model, predicting the confidence coefficient of each category mapped to the independent station commodity category system, selecting a plurality of categories with high confidence coefficients as candidate categories, and converting the confidence coefficients into weights; corresponding to candidate commodities in a commodity candidate list recalled according to the plurality of translation words, weighting predicted scores of target categories to which the candidate commodities belong in a commodity category system by using weights to determine sorting scores; and selecting target commodities from the candidate commodities according to the sorting score to form a commodity recommendation list. Therefore, the commodity better matched with the intention of the user can be obtained by compatibility with ambiguity during query word translation.

The invention discloses a big language model enhanced reordering complementary product recommendation method and device, and relates to the technical field of intelligent commodity recommendation. Comprising the steps that 1, output data of a baseline recommendation model are obtained, and the output data comprise K candidate complementary product lists for given products and initial correlation scores of the complementary products and the given products; 2, constructing structured prompt information, wherein the prompt information comprises detailed information of a given product, attribute description of each candidate product, historical interaction data of a user and context information; 3, inputting the structured prompt information into a pre-trained large language model, and evaluating the complementarity of each candidate product through a designed prompt template guide model; 4, analyzing the correlation score of each candidate product based on the output of the large language model, wherein the score reflects the complementation degree of the candidate product and the given product; and 5, reordering the candidate product list according to the correlation score to generate a final recommendation result.

Methods, apparatus, systems and articles of manufacture are disclosed for text extraction from a receipt image. An example non-transitory computer readable medium is disclosed comprising instructions that, when executed, cause a machine to at least generate a baseline product hierarchy using product information, calculate categorical impact values for products in the baseline product hierarchy, calculate an average impact value for the baseline product hierarchy using the calculated categorical impact values, calculate a first weighting factor for respective ones of the products based on a comparison between the categorical impact values and the average impact value, calculate a second weighting factor associated with respective ones of the products in the baseline product hierarchy based on sales data, and generate final weighted categorical impact values based on (a) the first weighting factors, (b) the second weighting factors and (c) the categorical impact values corresponding to the respective ones of the products.

A product planning system and method that can plan new products that do not exist in the world based on evaluations of existing specific products and combinations of technologies. and, Product Planning Program M provide. [Solution] The product planning system 10 includes a product information collection means 12a that collects product information about specific products via the Internet, and a product information generation means 12b that generates new product information NPI about new products different from the specific products based on a combination of the collected product information. The product information includes product evaluation information PVI about evaluations of the specific products and product technical information PEI about the technology of the specific products. The product information generating means 12a can generate, as new product information NPI, information based on products having the same product evaluation information PVI but different product names, and information based on products having the same product technical information PEI but different product names. .

The present disclosure provides a method, device, equipment and readable storage medium for determining the target attributes of a product, including: obtaining at least two product attributes corresponding to a product category; determining a combination of product attributes based on the product attributes, and determining a product group based on the combination of product attributes; grouping the commodities of the category according to the product group, and determining the target attributes in the product attributes according to the information of the commodities included in the product group. The method, device, equipment and readable storage medium provided by the present disclosure can classify commodities according to product attributes, and analyze the information of the commodities included in each group to determine the target attributes. The method, device, equipment and readable storage medium provided by the present disclosure do not rely on human factors, but analyze based on the information of the commodity itself, and the obtained results are more accurate, so as to guide the product manufacturer to carry out product research and development.

Methods, apparatus, systems and articles of manufacture are disclosed for text extraction from a receipt image. An example non-transitory computer readable medium is disclosed comprising instructions that, when executed, cause a machine to at least generate a baseline product hierarchy using product information, calculate categorical impact values for products in the baseline product hierarchy, calculate an average impact value for the baseline product hierarchy using the calculated categorical impact values, calculate a first weighting factor for respective ones of the products based on a comparison between the categorical impact values and the average impact value, calculate a second weighting factor associated with respective ones of the products in the baseline product hierarchy based on sales data, and generate final weighted categorical impact values based on (a) the first weighting factors, (b) the second weighting factors and (c) the categorical impact values corresponding to the respective ones of the products.

This invention discloses a product diversity complementary recommendation method in the field of e-commerce. The method includes: inputting the product category label of the target product into a pre-trained large language model to determine the complementary relationship between the target product and candidate products; constructing a product complementarity graph by treating products as nodes and the complementary relationship between the target product and candidate products as edge information; establishing neighbor relationships for the target product based on the product complementarity graph, combining the feature vectors and edge information of neighbor nodes; learning the product embedding representation through a graph neural network based on the neighbor relationships to determine the product embedding vector; determining the set of neighbor nodes for the target product based on the similarity between product embedding vectors; weighting intra-class complementarity and inter-class complementarity to select multiple product neighbors from the target product's set of neighbor nodes; and performing a self-balancing re-ranking of the comprehensive scores of the product neighbors through a constructed relevance-diversity weight mechanism to obtain the final recommendation result.

The invention provides an electromechanical product design cognitive scheme generation method and system based on a pre-training model. The method and system are used for solving the problem that the efficiency of a design scheme of a complex engineering problem product is low. The method comprises the following steps: identifying improvement parameters and deterioration parameters from an engineering problem text of a target mechanical and electrical product; querying an invention principle number from a pre-constructed contradiction matrix knowledge base according to the improvement parameter and the deterioration parameter, wherein the contradiction matrix knowledge base stores a mapping relationship between the improvement parameter and the deterioration parameter and the invention principle number; querying the invention principle information corresponding to the invention principle number from an invention principle knowledge base, wherein the corresponding relationship between the invention principle number and the invention principle information is stored in the invention principle knowledge base; and reasoning the engineering problem text and the invention principle information through the pre-training language model to obtain a design cognition scheme of the target mechanical and electrical product.

To automatically identify a sequence of recommended account / product pairs with highest likelihood of becoming a realized opportunity, an account / product sequence recommender uses an account propensity (AP) model and a reinforcement learning (RL) model and target engagement sequence generators trained on historical time series data, firmographic data, and product data. The trained AP model assigns propensity values to each product corresponding to received account characteristics. The trained RL model generates an optimal sequence of products that maximizes the reward over future realized opportunities. The target engagement sequence generators create target engagement sequences corresponding to the optimal sequence of products. The recommender prunes the optimal sequence of products based on the propensity values from the trained AP model, the completeness of these target engagement sequences, and a desired product sequence length. The recommender uses the remaining products, validated on three models, for account / product recommendations.

The utility model discloses a fool-proof device for a mechanical pressure maintaining clamp. The fool-proof device comprises a micrometer head, a micrometer head stop block, a side pushing clamp, a product base and a tool base. The product base is installed on the tool base, and the product is arranged on the product base. The pair of side pushing clamps are installed on the tool base in a sliding mode, the pair of side pushing clamps are located on the two sides of the product base respectively and slide relatively, and the pair of pressure maintaining profiling blocks are detachably installed on the sides, close to the product base, of the pair of side pushing clamps respectively, so that the pair of pressure maintaining profiling blocks can abut against the two sides of a product through the pair of side pushing clamps respectively; the micrometer heads are arranged on the side pushing clamps respectively, the micrometer head check blocks are fixedly arranged on the tool base respectively, and the micrometer head check blocks are located between the micrometer heads and the product base so that the micrometer heads can abut against the micrometer head check blocks. The utility model relates to the technical field of pressure maintaining equipment, and can solve the problem that a mechanical pressure maintaining clamp in the prior art cannot ensure the consistency and the stability of pressure maintaining force.

This application provides a product recommendation method, apparatus, device, medium, and program product, relating to the field of artificial intelligence. The method includes: determining the dynamic characteristics of a customer based on historical data of the customer's use of application software; determining the static characteristics of a customer based on the customer's attribute information; determining the static characteristics of a product based on the product's attribute information; determining the dynamic characteristics of a product based on the product's click and purchase records; pairing the customer and product based on their dynamic and static characteristics to obtain customer-product pairs; inputting the dynamic and static characteristics of the customer-product pairs into a pre-trained matching probability determination model to obtain the matching probability of the customer-product pairs; and recommending products to the customer based on the matching probability of each customer-product pair. This application accurately characterizes the features of customers and products through dynamic and static dual-dimensional information. Based on this, the matching results of customers and products are input into the model, resulting in more accurate and reliable matching probabilities.

The present invention relates to a method for calculating the propagation impact intensity of multi-source adaptive changes in products based on path coupling, and belongs to the field of engineering change technology. The method constructs a product adaptive change propagation network based on the propagation impact relationship between product parts, identifies the coupling nodes and coupling paths of multi-source adaptive change propagation, determines the correlation of the structural change attribute changes of the corresponding parts caused by the coupling nodes when they are affected by the propagation of different change sources, calculates the direct propagation impact intensity of the front-end nodes of the coupling path on the back-end nodes during multi-source changes, and calculates the propagation impact intensity of multi-source adaptive changes in products based on the correlation of the coupling paths, the direct propagation impact intensity of the coupling nodes, and the complexity of the changes of the parts. The present invention can effectively identify the coupling nodes and coupling paths of multi-source adaptive changes, improve product design efficiency, reduce change costs, and provide a basis for adaptive changes in the process of product customization.

The invention discloses a combustor management system, method, equipment, medium and product based on skid-mounted design, and belongs to the technical field of combustor management systems, and the combustor management system comprises an operation control module, a logic control module and a field module; the operation control module sends an operation instruction to the logic control module, the logic control module sends a control signal to the field module, the field module returns a detection signal to the logic control module, and the logic control module returns a feedback signal to the operation control module. The device is convenient to install and maintain, the device can be put into use only by connecting an external public engineering pipeline and an electrical signal line on site due to the skid-mounted design, the field installation workload is greatly reduced, the construction period is shortened, and subsequent maintenance and management are facilitated. The control performance is optimized, the local control cabinet and the DCS cooperate in a division mode, rapidity and independence of ignition and safety interlocking are guaranteed, centralized management of process optimization is achieved, and the overall control effect is better.

This application relates to the technical field of product research and promotion, disclosing a method and system for research and promotion based on shared information. The method comprises the following steps: obtaining user session shared information; identifying user behavior patterns based on the session shared information, specifically identifying the user's browsing and purchasing behavior patterns; obtaining the user's high-intent products based on the browsing behavior patterns; obtaining the user's associated intended products based on the purchasing behavior patterns; and promoting products to the user based on the high-intent products and associated intended products. This application can provide in-depth user behavior analysis, thereby improving the accuracy of product recommendations and facilitating the optimization of product promotion strategies.

A new product demand prediction apparatus according to the present disclosure includes: a memory configured to store instructions; and one or more processors configured to execute the instructions to: acquire new product information including at least information regarding promotion of a new product that is a target of demand prediction; acquire first similar product information indicating a sales performance of a first similar product selected based on at least one element of a scale of the promotion, a characteristic of a product, and a sales method; acquire second similar product information indicating a sales performance of a second similar product selected based on the category of the product; and predict sales in a predetermined period including a period after a promotion period of the new product based on the new product information, the first similar product information, and the second similar product information.

The present application proposes a method and device for determining commodity category information, wherein the method for determining commodity category information includes: obtaining multiple first target product words corresponding to sample commodities, constructing a commodity category system based on the hierarchical relationship between the first target product words, and determining the category information of the commodity to be matched according to the commodity category system. The product word of a commodity is used to define the commodity and can reflect the category and essential attributes of the commodity. The method constructs a commodity category system based on the product word of the commodity. The constructed commodity category system contains the category information of all sample commodities. These categories are divided based on the definition of the commodity itself and can be better applied to other new e-commerce scenarios such as search and recommendation. The commodity to be matched can be matched with the category information of the sample commodity based on the commodity category system, thereby determining the category information of the commodity to be matched and reducing the cost of determining and updating the commodity category information.

The invention relates to the technical field of engineering quantity calculation, in particular to a road engineering quantity calculation and statistical method and system based on a BIM model and a program product. The method comprises the following steps: defining a data structure comprising a basic quantity and an engineering quantity of a design component in a BIM model; calculating the basic quantity of a design component in the BIM model; binding at least one self-defined engineering calculation quantity calculation rule with the basic quantity in the data structure of the design component in advance; when the engineering calculation quantity calculation rule is called, matching the engineering calculation quantity calculation rule with the design component, and calculating the engineering quantity of the design component; the engineering quantity calculation rule comprises a material engineering quantity calculation rule, a manual engineering quantity calculation rule and a mechanical engineering quantity calculation rule. Through the configurable rule, a user is supported to customize the calculation rule according to the project requirement, the problem of rule solidification of traditional software is solved, the calculation result is accurately matched with the service reality, and the data accuracy and availability are remarkably improved.

To provide a product suggestion method, program, and device that minimize the burden of customer registration procedures and can introduce useful product information tailored to the characteristics of each customer. [Solution] The product proposal method includes a customer identification information acquisition step of acquiring SNS identification information on an SNS registered by the customer; a customer attribute information acquisition step of acquiring customer attribute information associated with the SNS identification information; a customer needs acquisition step of acquiring needs information indicating the customer's needs; a product information acquisition step of acquiring product information relating to a group of products to be offered to the customer; and a product identification processing step of identifying and presenting to the customer proposed products based on the customer attribute information, needs information and product information using a natural language model 5 that performs natural language processing.

The present invention provides a component location determination method and system, comprising: obtaining product model information of a product corresponding to a target order; matching a target product model process rule from a preset product model process rule database based on the product model information, wherein the target product model process rule includes component attribute information of the product; obtaining material type information of the components required for the product based on the target product model process rule, and determining the components required for producing the product based on the material type information; and obtaining installation location information for each component from a corresponding bill of materials in the target product model process rule based on the component attribute information, based on the hierarchical structure type of the target order. The present invention improves the accuracy and production efficiency of intelligent manufacturing processes.

The system according to the embodiment aims to enable salespeople to efficiently recommend optimal products. [Solution] A system according to an embodiment includes a reception unit, an analysis unit, and a recommendation unit. The reception unit receives requests in natural language. The analysis unit analyzes the requests received by the reception unit and analyzes past proposals or customer data. The recommendation unit recommends products based on the data analyzed by the analysis unit.

To provide a system for supporting marketing with consideration given to competing products.SOLUTION: An estimation system 0 for estimating a degree of variation in a product market share according to trends in a market in which a product group consisting of a plurality of products is sold, includes: an acquisition part of an estimation terminal device for acquiring sales data of the product group, including latest back product sales for every product; a setting part for setting a period of a market life cycle; a product sales calculation part for receiving input of a predicted growth rate of the latest market sales, and using a calculation formula according to periods of the life cycle to calculate an amount relating to future sales for every product based on the predicted growth rate of the market sales and the latest sales for every product; and a share value calculation part for calculating a latest share value representing the latest market share rate for every product based on the latest sales and the latest market sales, and calculating a future share value representing the future market share rate for every product based on the amount relating to the future sales and the future market sales calculated from the latest market sales and the predicted growth rate.SELECTED DRAWING: Figure 2