102 results about "Product selection" patented technology

The invention relates to the field of data processing, and provides a cross-border e-commerce intelligent product selection system and method based on multi-platform data fusion, and the method comprises the steps: carrying out the data collection and preprocessing of a plurality of cross-border e-commerce platforms, constructing a neural network model through optimal hyper-parameters, training, and generating a selected product recommendation list. Meanwhile, the structural parameters and the search direction of the selected product model are continuously updated, and the selected product recommendation list is dynamically updated. According to the system, multi-platform commodity data are integrated, versioning feature snapshots are constructed, hyper-parameter selection of a multi-snapshot version evaluation strategy optimization model with a consistent time sequence is adopted, the generalization ability of a commodity selection model to a time-varying data environment is enhanced, the possibility that the accuracy of the model is reduced due to the change of data distribution is reduced, and the accuracy of the commodity selection model is improved. Meanwhile, dynamic updating of the selected product recommendation list is achieved, and it is ensured that the recommendation strategy can be fully matched with preference migration of the selected product trend.

A system to personalize a shopping experience in a conversational commerce platform is disclosed. The system includes a processing subsystem having a user interface module for consumer input and an input conversion module that processes and translates this input using a large language model (LLM) engine. The engine module features a catalog facet creation module that structures product information, a facet enrichment module for detailed descriptions, images and buyers' profile, and a customer profiling module utilizing natural language processing to understand customer needs. An AI merchandising module presents optimal product facets to customers based on profiles and historical data. Additionally, a conversational commerce module facilitates product selection through guided conversations, while a personalization module tailors recommendations. The system also includes a data collection and analytics module for performance tracking and a training and optimization module for continuous improvement of the LLM.

The invention relates to the technical field of online sales, and discloses a healthy retail supply chain optimization method and device and computer device.The method comprises the steps that multi-level semantic analysis is conducted on obtained text data through a natural language processing technology, and potential demand keywords of a user are extracted; constructing a user portrait based on the user potential demand keyword and the user behavior data; grouping the users based on a preset grouping standard and the user portraits in the health scene, screening corresponding required health products for different user groups, and optimizing and adjusting the required health products in combination with market trend data in the user behavior data to obtain an adjusted product selection pool; and calculating a matching degree between the user and a preset candidate social platform based on the user portrait and the product selection pool, and generating a social platform recommendation list based on the matching degree. According to the method, multi-source heterogeneous data are integrated, potential demands of users are mined by using a large model, a product selection pool is optimized, and accurate recommendation and personalized marketing are realized in combination with user portrait analysis.

The invention discloses an interactive commodity selection method and system based on augmented reality, and relates to the technical field of augmented reality interaction, and the method comprises the steps: obtaining the commodity three-dimensional information of a target commodity and the commodity attribute information corresponding to the commodity three-dimensional information; determining scene reference coordinates of the augmented reality scene and ambient light features matched with the scene reference coordinates according to the spatial perception data of the terminal device, and generating an augmented reality presentation object of the target commodity in the augmented reality scene; obtaining interaction behavior data according to the interaction action of the user in the augmented reality scene; performing association matching on the interaction behavior data and the commodity attribute information to generate a candidate commodity selection feature set; and according to a preset fusion criterion, performing fusion on the candidate product selection feature set to obtain a target product selection decision, and outputting interaction feedback information corresponding to the target product selection decision. According to the application, robust fusion and reliable decision of multi-modal interaction information are realized, and the accuracy and interaction consistency of an augmented reality product selection process are improved.

The invention relates to an e-commerce live broadcast intelligent item selection method and system. The method comprises the following steps: S1, constructing a multi-dimensional commodity selection criterion system, and collecting original data of a to-be-recommended commodity under each criterion; step S2, subjective weight calculation; s3, objective weight calculation; and S4, carrying out weight fusion and scheme evaluation. According to the method, weight quantification verification is performed through the analytic hierarchy process and the entropy weight method, and the fusion coefficient is dynamically adjusted in combination with the business scene, so that the problems of subjective experience contradiction, poor cold start adaptability and low decision transparency of traditional product selection are solved, and an experience quantification-data verification-weight fusion decision chain is formed; and finally, the product selection scientificity is improved, the scene adaptability is enhanced, and the decision transparency is improved.

The invention discloses an e-commerce platform product selection and pricing method based on multi-agent reinforcement learning, aiming at the game decision problem between an e-commerce platform and a supplier, a platform agent and a supplier agent are constructed, the platform agent uses a deep Q network DQN to learn a product selection strategy, and the supplier agent uses an Actor-Critic algorithm to learn a pricing strategy. Through Stackelberg master-slave game modeling, a platform is used as a leader to make a decision for selection, and a supplier is used as a follower to make a decision for pricing after observation. A state space (including commodity sales volume, inventory, user score, supplier fulfillment rate and the like), an action space (discrete commodity selection and continuous pricing) and a multi-target reward function (balance profit, user satisfaction, inventory turnover and the like) suitable for an e-commerce scene are designed. The strategies of the two parties are converged to game equilibrium through alternate training, and online continuous learning is supported to adapt to a dynamic market environment. Experiments show that compared with an existing method, the method has the advantages that the overall income can be improved by 18-30%, the win-win situation of the platform and the suppliers is achieved, and the blank of multi-agent reinforcement learning in e-commerce product selection and pricing scenes is filled.

The invention discloses an intelligent article selection scoring system based on fusion of a rule engine and machine learning. The system comprises a data preprocessing unit, a feature engineering unit, a hybrid calculation unit and a dynamic weighted fusion unit. The feature engineering unit is used for generating a feature data set, a statistical feature data set, a time sequence feature data set and a composite feature data set from the preprocessed intelligent product selection data; the hybrid calculation unit is used for synchronously executing preset business rule calculation and machine learning prediction; preset business rule calculation is completed through a business rule calculation function, and machine learning prediction is completed through a multi-dimensional linkage machine learning prediction model; and the dynamic weight fusion unit is used for fusing the preset business rule score and the machine learning prediction score according to the dynamic business rule weight factor, and finally obtaining an intelligent product selection score. According to the invention, scientific, automatic and high-precision commodity potential evaluation is realized, and a breakthrough technical framework is provided for the field of e-commerce commodity selection.

The invention relates to the field of product selection service management, and discloses a product selection service management method and system based on real-time big data calculation, and the method comprises the steps: combining the current behavior data of a user with the historical behavior data, analyzing the preference of the user, recognizing a product preferred by the user, and carrying out the calculation of the product selection service. By analyzing the similarity between the product and the product interested by the user, the product closely associated with the user is screened out, and by analyzing the whole process of the user from product contact to final purchase, the behavior path of the user is tracked in real time, so that the user experience is improved. Based on comprehensive analysis of a user preference analysis result, a product association analysis result and a user behavior path analysis result, all related products meeting user requirements are screened out, and the screened products meeting the user requirements are sorted and recommended, so that a more comprehensive and more personalized recommendation strategy can be formulated, and the user experience is improved. The accuracy and effectiveness of recommendation are improved, and diversified requirements of users are met.

The invention discloses a machine learning-based cross-border e-commerce self-operation product selection dynamic adjustment method and system, relates to the technical field of e-commerce product selection adjustment, and aims to construct a product selection adsorption quantity model, evaluate the sales attraction of different products in different market situations, analyze the market response condition of each product and improve the product selection efficiency. After the commodities are screened in combination with the output result of the commodity selection adsorption quantity model, the commodities are adaptively adjusted, the racking sequence is determined, the market response condition analysis result is sent to the dynamic optimization module, and based on the market response condition analysis result of the commodities, the discount strength of the commodities is dynamically adjusted by simulating the market dynamic state; according to the analysis of commodity sales data and market feedback, the shelf sequence and marketing promotion strategy of commodities are optimized. According to the adjustment method, through introduction of a machine learning technology and combination of a data driving mode, commodity sales data and market environment changes can be analyzed from multiple dimensions, and commodity selection and adjustment efficiency of a cross-border e-commerce platform is significantly improved.

Provided in the embodiments of the present disclosure are a product information generation method and apparatus, and a device and a computer program product. The method comprises: acquiring a generation request for product information, wherein the generation request at least comprises a category description corresponding to the product information, and at least one knowledge item description; on the basis of the category description and at least one knowledge item description in the generation request, determining a product category that matches the generation request, and a concept attribute under each knowledge item under the product category; on the basis of the product category and the concept attributes, performing product selection analysis, so as to obtain preliminary product information, wherein the preliminary product information at least comprises a recommended product corresponding to the generation request, and a user profile corresponding to the recommended product; and on the basis of the preliminary product information, generating product information corresponding to the generation request, wherein the product information at least comprises description information of a product and promotional copy for the product. The embodiment not only reduces manpower and material resources required for generating product information, but also improves the quality and efficiency of product information generation.

The invention discloses a commodity information display method and device, a commodity information acquisition method and device, electronic equipment and a storage medium, in the commodity information display method, to-be-combined commodity information and combined commodity summary information are acquired, and then a to-be-combined commodity selection trigger control and a plurality of combined commodity selection trigger controls can be displayed on a to-be-combined commodity detail page. The combined commodity selection trigger control at least displays a thumbnail of a combined commodity main image and combined commodity selection cost information, and the to-be-combined commodity selection trigger control at least displays a thumbnail of a to-be-combined commodity main image; therefore, style information and purchase cost information of selectable combined commodities can be conveniently checked on the to-be-combined commodity detail page, style information of selectable to-be-combined commodities can be checked at the same time, and a user can conveniently decide whether to select the combined commodities or not based on a combined commodity selection trigger control and a to-be-combined commodity selection trigger control. And thus, the purchasing efficiency of the multiple commodities is improved.

1. The name of the design product: financial product transaction selection graphical user interface of electronic device. 2. The use of the design product: an electronic device. 3. The design points of the design product: the interface content of the graphical user interface in the electronic device. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: the graphical user interface is used for users to select the transaction product when conducting financial transactions, and displays the brief information of the financial transaction product. 6. The human-computer interaction mode of the graphical user interface: the front view is the structural bill product selection interface of the financial transaction platform, and the interface displays product brief information. The user clicks the product brief information card in the interface to select the corresponding product for transaction. The user slides the front view interface curtain upwards, and the interface changes to the interface change state view. The interface displays pre-sale product information. XXX in the interface represents the text content.

Computer-implemented manufacturing and sales strategy planning process that includes: a reserve production capacity determination step to determine, based on information related to a sales plan of a multitude of products and a production capacity of a production plant to produce each of the multitude of products, whether a reserve production capacity of the production plant exists in relation to the sales plan for each of the products; an improvement effect calculation step for applying one of a variety of profit improvement strategies according to the availability of reserve capacity to each of the products for which the availability of reserve capacity was determined in the reserve production capacity determination step, and calculating an improvement effect for each of the products to which each of the profit improvement strategies was applied; a product selection step to select, based on each calculation result obtained in the improvement effect calculation step, a specific product from the multitude of products on which the improvement effect has exceeded a set value in connection with each of the multitude of profit improvement strategies; an element extraction step to extract for each of the profit improvement strategies of an element that meets a limiting sales or production condition of the specific product, which is set in the product selection step, and which produces the specific product; and a manufacturing and sales strategy selection step for planning a manufacturing and sales strategy in relation to the elements extracted in the element extraction step, and selecting one or more specific element strategies based on the improvement effect, wherein a supply and demand plan is simulated by reflecting on the improvement effect of the selected strategy, and whereby Each calculation result obtained in the improvement effect calculation step is displayed or output by means of a display unit (50), wherein the display unit (50) presents the user with the improvement effect based on the content of the manufacturing and sales strategy of each element in order to promote user consensus based on objective evidence, wherein The computer-implemented manufacturing and sales strategy planning process further includes a step to simulate a strategy scenario pattern by setting parameters by the user, and wherein The display unit (50) shows a quantitative estimate result for the user's decision-making process.

The utility model discloses a protective film for uncovering, which belongs to the technical field of protective films and comprises a release layer, a PI (polyimide) substrate layer, a thermosetting adhesive layer, a PET (polyethylene terephthalate) composite film layer and a release layer which are sequentially stacked from top to bottom. Compared with the prior art, the utility model has the following beneficial effects: a five-layer structure is adopted, PI is used as a base material, the outer layer of the base material is coated with the release layer, the middle layer is the thermosetting adhesive layer, and the lower surface is the PET composite film layer of which the outer layer is coated with the release layer, so that the uncovering position is flexible and changeable, the uncovering can be opened at any position of the PI surface or the PET surface, and the product selection of a user is facilitated; necessary conditions are provided for PCB / FPC automatic lamination production; in addition, the thermosetting adhesive layer is used for replacing the original acrylic adhesive layer, so that the product quality is more stable, the production modes are diversified, and the capacity of adapting to various external environments is stronger.

A product dispensing machine includes a user interface configured to receive user selections and to present user selectable options. The product dispensing machine also includes a controller configured to control the user interface to present user selectable options in order of priority. The controller is configured to aggregate the user selections and to dynamically adjust the priority of the user selectable options based on the aggregated user selections.

To easily install an expansion unit for a main unit additionally.SOLUTION: Provided is an automatic selling device 1 including: a main unit 10 including a main control unit 20 that controls operations of a commodity selection unit 16 and a payment processing unit 18; and an expansion unit 30 including an expansion unit body 31 that stores commodities therein and has a front opening 31a to be opened / closed by an outer door 32. The automatic selling device is configured such that one or more of the expansion units 30 are connected to the main unit 10. The expansion unit 30 includes an outer door opening / closing detection unit 35 that detects an opened / closed state of the front opening 31a by the outer door 32, and a unit control unit 40 that controls ejecting of a commodity. When an expansion unit identification setting mode is brought about by an input operation in a remote controller 14, the main control unit 20 distributes an identification address to the relevant unit control unit 40 in accordance with the order of detection of the opened / closed state by the outer door opening / closing detection unit 35.SELECTED DRAWING: Figure 2

The invention discloses a commodity recommendation method and system, a storage medium and electronic equipment, and the method comprises the steps: obtaining the multi-modal data of a to-be-recommended commodity, and carrying out the normalization and feature extraction processing of the multi-modal data, so as to obtain the features of the multi-modal data; determining a data change feature and a user preference evolution feature according to the multi-modal data feature, and fusing the multi-modal data feature, the data change feature and the user preference evolution feature through a preset fusion mode to obtain a fused feature vector; determining a profit rate prediction value of the to-be-recommended commodity in the target scene according to the fusion feature vector and the multiple scene labels; and determining a target commodity combination according to the profit rate prediction value and a preset constraint condition. According to the method, by obtaining the multi-modal data and integrating and fusing the multi-modal data, the problem that product selection prediction and actual requirements are disjointed due to a single data dimension is solved, and thus the product selection accuracy is improved.

The present disclosure provides a regional supply object screening method, device, equipment and medium, the method comprises: obtaining a trained target regional supply object screening model of a target supply region; obtaining a candidate supply object of the target supply region, and based on the target regional supply object screening model, obtaining a predicted allocation rate and a predicted supply amount of the candidate supply object in the target supply region within a predicted time range; and screening a target supply object of the target supply region from the candidate supply object according to the predicted allocation rate and the predicted supply amount. The adaptation degree between the target supply object and the target supply region is improved, the waste of the product selection quota of the target supply region is avoided, the screening efficiency of the target supply object of the target supply region is improved, the possibility of the target supply region achieving the category operation target of the headquarters is improved, and the product selection method and product selection effect of the offline store as the target supply region are optimized.

To prepare a shelf allocation pattern which makes the best use of the experience of a person in charge of shelf allocation and does not give an unnatural feeling by using a general information processor.SOLUTION: In this shelf allocation pattern automatic preparation method, the shelf information and merchandise information of an existing shelf allocation pattern and a shelf allocation pattern to be prepared (called preparation pattern) are inputted to an arithmetic means, the automatic preparation processing of the shelf allocation pattern is performed, and the preparation pattern is outputted. The input data to the shelf allocation pattern automatic generation processing includes information on a commodity group (referred to as a minimum granularity continuous commodity group) included in the same attribute of the lowest layer when commodities are classified into a hierarchical structure by attributes in the existing shelf allocation pattern and continuous in one stage of the shelf, and the attribute arrangement processing for arranging the commodities according to the hierarchical structure of the attributes of the commodities and the commodity selection and arrangement processing for selecting and arranging the commodities in the lowest layer attribute are performed. In the commodity selection and arrangement processing, commodities included in the minimum granularity consecutive commodity group are continuously arranged in one stage of the shelf.SELECTED DRAWING: Figure 1

The present disclosure provides a combination product selection method, system and electronic device based on the FP-Growth algorithm, applied to tourism commodity combination recommendation, by obtaining historical tourism order data, and preprocessing the historical tourism order data, the same attribute tourism commodity item is classified into the same preset tourism commodity category, and a shopping basket data set is generated; the minimum support threshold and the maximum combination length threshold are set, based on the minimum support threshold and the maximum combination length threshold, the candidate frequent item set is obtained from the shopping basket data set according to the FP-Growth algorithm; the association of the tourism commodity combination in the candidate frequent item set is evaluated, and the target tourism commodity combination is selected. In this way, the error caused by subjective misjudgment is avoided, the product selection decision is more scientific and objective, and the "real commodity association" and "random co-occurrence of popular commodities" are effectively distinguished, which can accurately mine the potential demand of users and improve the user experience and satisfaction.

We provide a trademark support system suitable for selecting goods or services. [Solution] The trademark support device 100 includes first to third product selection processes. Users can select and use the functions related to the first to third product selection processes from a menu. In the first to third product selection processes, based on information from a common product list, if the relevant product (service) is registered in the product list, the corresponding product selection checkbox is checked when the product (service) is displayed. This allows the user to select a product (service) from the display results obtained by the other functions, taking into account the product (service) obtained by one of the functions related to the first to third product selection processes.

The application is suitable for the cross-border e-commerce technical field, and particularly relates to a cross-border e-commerce full-automatic product selection and listing method, system and device based on multiple platforms, which comprises the following steps: obtaining target information; wherein the target information comprises a target region and a target platform; obtaining preselected product information based on the target information; wherein the preselected product information comprises at least one preselected product name; obtaining listing product information based on the preselected product information and the target platform; wherein the listing product information comprises at least one listing product information, and the listing product information comprises a listing product name, a listing product picture and a listing product price. The cross-border e-commerce full-automatic product selection and listing method, system and device based on multiple platforms can improve the problem that the analysis, product selection and listing are performed by manual work, the listing period is long, and it is difficult to capture dynamic market demand, which may miss the market opportunity.

An object of a system according to an embodiment is to confirm an environmental influence due to a purchase activity of a user and to promote product selection in consideration of sustainability.SOLUTION: A system includes an environmental influence confirmation part, a point use part, and a recommendation part. The environmental influence confirmation unit confirms the environmental influence due to the purchase activity of the user. The point using section uses the points obtained in the transaction to purchase the eco-friendly commodity. The recommendation unit recommends a product selection in consideration of sustainability.SELECTED DRAWING: Figure 1

The application relates to the technical field of artificial intelligence, and discloses a method, device and system for product selection scheme generation and a storage medium. The method comprises the following steps: performing semantic analysis on current product demand information, and extracting a current demand vector, wherein the demand vector comprises fields corresponding to one or more element information in a scene label, a technical parameter list, a constraint condition key-value pair and a regional adaptation requirement; based on a large language model, a current demand vector is disassembled according to a thinking chain guide mechanism, and a corresponding current product selection scheme component list is obtained, wherein the component list comprises one or more of function information, technical parameter information and adaptation standard information of each component; current product information matched with the current product selection scheme component list is searched from a set product database, and a corresponding structured current product selection scheme is generated. In this way, a complete scheme covering "architecture-product-guarantee" is generated, which is suitable for the demand of Chinese industry cooperation in overseas market.

A valid combination of products is constructed from a set of products identified by a retailing backend system. The valid combination satisfies a condition of an offer. A product in the combination of product is a physical product located in a physical store. A social sentiment towards the product in social media data of a shopper is evaluated, and a rating of the product is computed using the evaluation. A location of the product in the store is obtained from the retailing backend system. The location of the product is overlaid on a view of the store, where the view is from a perspective of a location of the shopper, the shopper being physically situated in the store.

The invention discloses an information recommendation method and system based on man-machine intelligence, and belongs to the technical field of communication, and the recommendation method comprises the following steps: carrying out the collection and analysis of the Internet surfing data of a target user, and obtaining a high-energy factor affecting the Internet surfing cost of the target user; determining a to-be-recommended product for the target user according to the high-energy factors and the usage amount corresponding to each high-energy factor; determining a final recommended product of the target user according to historical recommendation results of the users of the same type; according to the method, in consideration of consideration of own demands, economic benefits and the like of the users, the users have different acceptance capacities on the recommended packages, so that in order to ensure the success rate of recommendation, the recommended products are adjusted by integrating choices of the users of the same type in historical data when the users accept the recommendation; therefore, benign guidance for user product selection is realized, and client maintenance and recommendation success rate improvement are facilitated.

These images are images that display the status of the mobile sales robot, etc. For example, "Reference image 1 showing the usage status" shows the manager that inventory adjustment is necessary, "Reference image 2 showing the usage status" shows the manager or purchaser that sales have been suspended, "Reference image 3 showing the usage status" shows the purchaser that product selection has been completed, and "Reference image 4 showing the usage status" shows the purchaser that product purchase has been completed.

1. The name of the design product: graphical user interface for displaying icons according to product packaging color on electronic device. 2. The use of the design product: the design product is used for an electronic device. 3. The design points of the design product: the graphical user interface displayed on the electronic device. 4. The picture or photo that best indicates the design points: interface change state diagram 1. 5. The use of the graphical user interface: the graphical user interface displayed on the electronic device of the design product is the product selection interface of the application software. The front view is the product selection interface. After the user clicks the corresponding product, the interface changes from the front view to interface change state diagram 1. Interface change state diagram 1 has a lower layer interface. The lower layer interface displays multiple product specification selection icons. The color of the product specification selection icon is the same as the product packaging color of the corresponding product specification. After the user clicks the corresponding product specification selection icon, the interface changes from interface change state diagram 1 to interface change state diagram 2. In interface change state diagram 2, the selected product specification selection icon changes color. After the user clicks the button in the lower right corner of interface change state diagram 2, the interface changes to interface change state diagram 3. 6. Other circumstances that need to be explained: the display screen panel is a conventional design, and other views are omitted.

According to the method, the device and the system for automatically acquiring the process duration in the SAP system and the computer storage medium provided by the embodiment of the invention, the product model of which the process duration needs to be acquired currently is received, then the rule code is acquired from the SAP system, and the rule code is analyzed to obtain the rule element list corresponding to the rule code; and then converting the rule element list into rule logic which can be identified by the PS system based on the rule element list, and obtaining a logic result, so as to judge whether the product type selection has the process duration or not, and automatically obtaining the process duration corresponding to the rule code under the condition that the process duration exists. Through the method, the device, the system and the storage medium, the process duration of product type selection in the SAP system is automatically obtained in the PS system, so that the method, the device, the system and the storage medium are applied to product type selection process simulation.

The invention provides a store item selection method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a target commodity category of a first store according to the obtained sales data of the first store in at least one commodity category and the sales data of a reference store in each commodity category, and carrying out the aggregation of the target commodity category according to a result of the aggregation of the target commodity category, the method comprises the steps of determining a first class of labels of a first store, determining at least one second store similar to the first store according to the first class of labels, determining commodities selected by the first store according to target commodities in the at least one second store, and determining the commodities selected by the first store based on sales data of the first store and sales data of a global reference store. According to the method, the target commodity category of the first store is determined, clustering is carried out according to the category of the first store obtained by aggregating the target commodity category so as to determine the second store similar to the first store, and the target commodity in the second store is used as the commodity selected by the first store, so that the accuracy of commodity selection of the stores is improved.