46 results about "Digital advertising" patented technology

A system and method for analyzing screen-recorded personalized digital content using on-device computer vision and generative AI. A user captures content from a recommender system interface, such as screen activity or browser-rendered content, optionally with concurrent voice commentary. On-device processing generates intermediate representations using CLIP-style embeddings, OCR text, and transcribed audio tokens, flagging advertisements, changes in content, diversity in content, and similarities in content. A compact generative AI model produces metadata summaries, which users may annotate with tags or comments. A composite metadata package is transmitted to a cloud system, while raw media is deleted. The invention enables privacy-preserving, bandwidth-efficient insight into recommender-based media and user feedback.

A method for celebrity-based advertising includes storing, in a server, a likeness of subject and a corresponding booking that includes parameters outlining availability of the subject for digital advertising. The method further includes receiving or creating, by the server, a pitch that falls within the parameters of the booking, the pitch corresponding to the subject. The method further includes receiving, by the server and from a first user device, a first image of the likeness of the subject or another likeness of the subject. The method further includes determining, by the server, that the image matches the likeness of the subject. The method further includes transmitting, by the server, the pitch to the first user device to be output by the first user device.

The application relates to the field of digital media playing monitoring, and discloses an outdoor digital advertising screen playing state monitoring and abnormality repairing method; the method generates a playing time sequence template according to advertisement scheduling and advertisement materials by a server; a broadcast control terminal collects broadcast control output evidence including a current advertisement segment identifier, a decoding frame timestamp, a rendering queue state, a video output interface state and a screen body control card feedback state when playing the advertisement materials; an image acquisition unit collects a screen display picture and forms screen display evidence; the server maps the playing time sequence template, the broadcast control output evidence and the screen display evidence to the same playing time axis to obtain scheduling consistency results, output consistency results and real display consistency results, and generates abnormality attribution results according to the conflict types among the three, and then corresponding repairing strategies are executed.

The invention relates to the technical field of digital advertisement putting, in particular to an intelligent advertisement playing terminal and a carousel control method thereof, and the method comprises the steps: collecting real-time environment parameters and real-time crowd characteristic parameters of an area where the advertisement playing terminal is located; inputting the attention concentration degree and the environment interference degree into a preset carousel strategy model, calculating the dynamic playing weight of each to-be-played advertisement in an advertisement library, and generating an initial carousel list according to the weight from high to low; acquiring historical playing data of each advertisement in the initial carousel list, optimizing the initial carousel list according to the historical playing data, generating a target carousel list, and controlling the terminal to play; and collecting playing effect data of the current carousel period, and adjusting parameters of the carousel strategy model according to the playing effect data. According to the invention, the pertinence and real-time response capability of advertisement playing are improved, and the dynamic optimization and adaptive adjustment of the carousel strategy are realized.

According to an embodiment of the present invention, a method and system to generate recommendation to place a set of digital advertisements is disclosed. The recommendation to place a set of digital advertisements is performed by, receiving a request to place the set of digital advertisements, integrating a digital content valuation as an input to a reinforcement learning agent, assigning a criticality factor for the digital content valuation, employing the reinforcement learning agent to match advertisements with relevant content environments, optimizing the advertisement placement algorithm, generating a recommendation for advertisement placement by the advertisement placement algorithm, wherein generating the recommendation includes matching advertisements with a relevant content environment, placing the advertisement based on the recommendation, and maximizing engagement and revenue generation.

This invention relates to the field of power line identification technology, specifically to a power line identification sign with display function, including a mounting plate and a multimedia screen. A protective shell is provided on the outside of the multimedia screen, and a quick-connect mechanism is provided between the protective shell and the mounting plate for quickly installing the protective shell on the side of the mounting plate. A reflective adjustment mechanism is provided between the multimedia screen and the protective shell to adjust the angle of the multimedia screen according to changes over time. This power line identification sign with display function effectively solves the reflection problem caused by fixed vertical placement of the sign through the reflective adjustment mechanism. The current control device can adjust the current through wires to control four current adjustment modules according to changes over time, changing the repulsive or attractive force between electromagnet one and electromagnet two, avoiding glare and uneven brightness caused by ambient light, reducing the risk of operational errors, ensuring the display effect of digital advertising content, and improving the reliability of information transmission.

A method for celebrity-based advertising includes storing, in a server, a likeness of subject and a corresponding booking that includes parameters outlining availability of the subject for digital advertising. The method further includes receiving or creating, by the server, a pitch that falls within the parameters of the booking, the pitch corresponding to the subject. The method further includes receiving, by the server and from a first user device, a first image of the likeness of the subject or another likeness of the subject. The method further includes determining, by the server, that the image matches the likeness of the subject. The method further includes transmitting, by the server, the pitch to the first user device to be output by the first user device.

The present invention provides an automated system (100) and method for tracking interactions, calculating payouts, and personalizing digital advertisement delivery to healthcare professionals (HCPs). The system (100) comprises an account management module (110) to verify user credentials, ensuring the user is a healthcare professional, and a consent management module (120) to record and store user consent on a secure, immutable ledger. A tracking module (130) logs user interactions with advertisements, capturing engagement data. The system (100) further includes a dashboard generation module (140) that displays engagement metrics, a personalization module (150) that delivers targeted advertisements based on user profile data, and a payout calculation module (160) to compute payouts based on engagement quality, advertisement demand, and predefined thresholds. A reward management module (170) provides incentives for HCPs to engage with content and participate in surveys.

The application relates to the technical field of digital advertising, in particular to a dynamic advertisement putting method based on end-side AI real-time content analysis. The application constructs a lightweight scene monitoring model based on an optical flow method and interframe difference, calculates the motion saliency of a video stream in real time, and triggers key frame extraction; a main analysis model is used to perform instance segmentation on the key frame, to generate a pixel-level mask and a refined boundary of a target subject, and to perform region-of-interest cutting and background elimination based on the mask; a hybrid semantic analysis model is used to extract explicit discrete labels and implicit high-dimensional visual feature vectors in parallel, to capture texture, material and style attributes of the target; end-side knowledge graphs and visual dominance scores are combined to perform semantic consistency verification and logic conflict resolution on the recognition result, to generate visual feature representation; finally, based on histogram analysis and edge detection, a visual interaction floating layer with adaptive transparency and a proper position is rendered on the video layer, and digital advertising is put to users.

A vending machine with an improved cabinet design is disclosed. The cabinet is constructed with a tapered configuration wherein the rear portion is narrower than the front, enabling optimal installation in architectural corners, against curved surfaces, or within circular floorplans. The machine comprises integrated audiovisual components, energy-efficient lighting, secure payment infrastructure, and modular connectivity for digital advertisement display and vending operations, along with other optional features. Optional features include AI-based product tracking, camera for security and / or product management (29) and a multi-use housing structure in the lower section of the machine that incorporates waste disposal (26) and / or print advertising (25). This invention expands both the placement flexibility and multifunctional capability of vending systems in constrained and high-traffic environments.

This invention relates to the technical field of digital advertising and discloses a digital advertising method and system based on virtual communities. The invention uses merchant virtual units to display digital models of target products, while customer virtual units can observe products from multiple dimensions. Based on the transaction records of the target products, offline observation information is obtained from the customer virtual units, and the product digital model is reconstructed accordingly, generating a set of measured reference models. By parallel matching of the product digital models of different merchants within the virtual community and the measured reference model set, a personalized temporary community scene is generated for the customer virtual units. Based on the customer's registration information, logistics delivery prediction is performed on the product information in the temporary community, generating a personalized product prediction model. This helps customers make more accurate shopping decisions. This method enhances the personalization and accuracy of advertising, improves the customer shopping experience and advertising effectiveness, and solves the problem of low advertising effectiveness in existing technologies.

The invention discloses an intelligent decision support method and system based on causal inference, and relates to the technical field of data analysis, and the method comprises the steps: reading the operation multivariate structure data of each historical digital advertisement service, finding and analyzing the causal structure of the operation multivariate structure data according to a mixed causal structure, and obtaining the causal structure of the operation multivariate structure data; establishing a causal directed acyclic graph of each digital advertising service; performing causal effect identification estimation according to an operation multivariate structure data causal structure in the causal directed acyclic graph, marking an effect state between causal variables, and establishing a causal directed weighted acyclic graph of each digital advertising service; and analyzing stability and heterogeneity between causal structures of each path in the causal directed weighted acyclic graph, substituting the stability and heterogeneity into the digital advertisement marketing causal decision model, and generating a causal influence decision support scheme of each digital advertisement service. The method has the advantages that a reliable basis is provided for optimal configuration and personalized marketing of advertisement resources, and the rate of return on investment and the operation efficiency are greatly improved.

The invention discloses a cross-platform advertisement putting budget dynamic distribution system, and relates to the technical field of advertisements, and the technical scheme is characterized by comprising the following steps: obtaining an initial budget distribution parameter of a current advertisement putting stage, and carrying out putting scene simulation according to the initial budget distribution parameter to obtain user behavior characteristic data; obtaining a reference conversion data value according to the historical budget distribution parameter and the historical conversion data; obtaining a conversion loss data value according to an association influence trend feature between the historical user behavior feature data and the historical conversion loss value; an actual conversion data value is obtained according to the reach increment, the active diffusion range and the conversion loss data value, the initial budget distribution parameter is dynamically optimized and adjusted according to the reference conversion data value and the actual conversion data value, and then an advertisement budget distribution management and control result is output, and the effect is that the method is suitable for complex and changeable digital advertisement putting scenes.

In some examples, a system comprises at least one programmable processor; and a machine-readable medium having instructions stored thereon which, when executed by the at least one programmable processor, cause the at least one programmable processor to execute operations comprising: receiving a first request from at least one user device to execute an instance of an application; transmitting a graphical user interface (GUI) to the at least one user device to be rendered on a display of the at least one user device; receiving a second request, via the GUI, from the at least one user device, to deploy a digital advertisement, the second request including a set of platforms of a plurality of platforms of a multi-platform integration system, a set of settings, a set of parameters, and a set of allocation data; interfacing with each one of the platforms in the set of platforms; and integrating a digital advertisement directly with each one of the platforms in the set of platforms based on the set of settings, the set of parameters and the set of allocation data.

A dynamic digital advertising content system having a front end system and a back end system, and used to present product content to a user's computing device in the form of a digital circular. The back end system provides retailers and third party access to upload, and update, product content information for the digital circular, including videos and animations. The dynamic digital advertising content system can include integrations for third-parties such as digital coupon providers and loyalty program providers. The system permits users the ability to share with other users merchandise displayed in the digital circular and / or selected for a shopping list. Such shared content can be dynamically arranged for subsequent presentation on a computing device of the recipient. The digital circular is further customizable for individual retailers or retailer locations, as well as customizable based on detected histories and / or characteristics of the user receiving the digital circular.

Some implementations relate to methods, systems, and computer-readable media for digital advertising within a virtual experience provided at a virtual experience platform. A user's avatar's viewpoint, perspective, time spent viewing, and other attributes are accurately tracked to determine an overall advertising impression. Different advertisements may be displayed to an avatar based on the avatar approaching a digital advertisement element and being within a threshold distance of the digital advertising element. Furthermore, metrics based upon user engagement may be tracked and associated with displayed advertisements.

This application discloses a method and system for dynamic allocation of CID attribution weights in multimodal advertising interactions, comprising the following steps: S1: Responding to an ad access request, collecting multimodal interaction behavior data, and associating and binding the multimodal interaction behavior data with the CID identifier to construct a triplet interaction dataset; S2: Inputting the multimodal interaction behavior data in the triplet interaction dataset into an intent depth quantification model, outputting an interaction intent depth value, and filtering out noisy interaction data with intent depth values ​​below a preset threshold; S3: Calculating the contribution weight of each effective interaction behavior to subsequent conversion events; S4: Receiving user conversion events, generating multi-dimensional attribution results, and mapping and storing the attribution results with conversion events. Belonging to the field of digital advertising technology, this structure can overcome the limitations of single click attribution, enabling the attribution results to more accurately reflect the user conversion path.

The invention discloses an advertisement feedback optimization method and device based on machine learning, and relates to the technical field of digital advertisements. The method comprises the following steps of: firstly, constructing a causal graph containing user characteristics, advertisement exposure, click and conversion, eliminating selection deviation caused by confusion variables by utilizing a dual machine learning model, and accurately estimating a condition average processing effect of advertisement putting; secondly, performing multi-contact attribution in combination with a conditional average processing effect and a Shapley value to generate an initial putting strategy, and dynamically updating the strategy by using real-time data through an incremental causal forest algorithm; and finally, screening high conditional average processing effect material features, generating a new idea by using a generative adversarial network, and feeding back the new idea to a delivery engine. According to the method, the problems of correlation deviation, inaccurate attribution and delayed creative optimization in traditional advertisement putting are solved, and the advertisement putting accuracy, the real-time response capability and the return on investment are remarkably improved.

The application provides a threshold privacy set intersection method and device and a readable storage medium thereof, and belongs to the technical field of privacy calculation and secure multi-party computation. In view of the problems of low batch selection efficiency, large calculation and communication cost of the existing scheme in large-scale two-party balanced set matching, the application encodes a plurality of selection indexes of a receiving party into roots of blind polynomials on a finite field, realizes batch selection expression and key generation through polynomial coefficient transmission, and completes polynomial batch inadvertent transmission expansion; the algebraic association relationship established in the inadvertent transmission expansion stage is reused as the key material of an inadvertent pseudo-random function, pseudo-random labels of local calculation elements are obtained by both parties, and light batch inadvertent pseudo-random function mapping is completed; finally, the size of the intersection set is safely calculated in the label space, and whether to output the accurate intersection set is determined according to the comparison result of the size and the threshold. The application is mainly used for digital advertising audience evaluation, joint marketing and anti-fraud risk control.

A digital advertising system for a physical commercial location includes multiple digital displays positioned within store aisles, each display associated with a product category and / or a location zone context. A cloud-based server manages advertisement inventory and performance tracking. The server's auction module receives bids from advertisers and selects winning bids for each display based on its product category and / or location zone context. A performance tracking module applies an econometric attribution method to assign sales uplift to displayed advertisements and an action-based attribution method using tracked shopper actions. The system delivers context-sensitive advertising and provides robust attribution of ad performance within physical retail environments.

This invention relates to the field of digital advertising and marketing technology, and discloses a blockchain-based interactive advertising incentive and data authorization supervision system and method, including an advertiser terminal, a user terminal, a blockchain notarization module, an access control module, and a smart contract module. Both the advertiser terminal and the user terminal are connected to the access control module, which in turn is connected to the smart contract module. The system abandons the traditional single display or click count of advertising and innovatively introduces a question-and-answer verification mechanism. Users must pay attention to complete the questions, and the entire process of displaying, answering, judging, and finally awarding prizes is recorded on the blockchain for notarization, fundamentally eliminating machine-generated traffic or invalid traffic. From ad creation, user interaction, question judging results to incentive flow, all key nodes are recorded with hash values ​​and a trusted timestamp through the blockchain notarization module. No party can unilaterally tamper with historical data, providing technical endorsement for the authenticity of advertising effectiveness.

The present invention is directed to a modular, multi-faceted digital advertising and surveillance device that integrates AI-driven facial recognition and demographic analysis to dynamically adapt content and security measures in real-time. The device features multiple high-resolution cameras, capacitive touchscreens, and advanced wireless communication capabilities, including geofencing, to deliver targeted advertisements and enhance security monitoring. The system is designed for various applications, including retail, transportation hubs, and hospitality environments, providing a versatile solution that merges advertising and surveillance into a single, cohesive platform.

The invention discloses a digital advertisement full-link putting optimization method and system based on a user life cycle, and relates to the technical field of advertisement putting, and the method comprises the steps: obtaining user basic information and digital advertisement information, obtaining target product information according to the digital advertisement information, and carrying out the binary classification of users based on the target product information and the user basic information, and obtaining basic classification information of the user. According to the method, binary classification is performed on the users through target product interaction behaviors, user life cycle evaluation indexes are constructed through behavior data, accurate classification of the users is realized by taking a user basic interaction strength coefficient as a benchmark, a stage basis is provided for subsequent targeted advertisement screening, and through a keyword preference coefficient, the user life cycle evaluation indexes are calculated. According to the method, accurate matching of the advertisement content and the user interest is achieved, dynamic adaptation of advertisement putting of different groups is achieved through the advertisement type preference coefficient and the advertisement feature preference coefficient, and the accuracy and reliability of advertisement putting are ensured.

The invention relates to the technical field of digital advertisements, in particular to a dynamic advertisement putting method based on end-side AI real-time content analysis, which comprises the following steps of: constructing a lightweight scene monitoring model based on an optical flow method and inter-frame difference, calculating the motion significance of a video stream in real time and triggering key frame extraction; performing instance segmentation on the key frame by adopting a main analysis model, generating a pixel-level mask and a refined boundary of a target main body, and performing region-of-interest cutting and background elimination based on the mask; adopting a mixed semantic analysis model to extract an explicit discrete label and an implicit high-dimensional visual feature vector in parallel, and capturing texture, material and style attributes of a target; performing semantic consistency verification and logic conflict resolution on an identification result in combination with the end-side knowledge graph and the visual dominance score, and generating visual feature representation; and finally, based on histogram analysis and edge detection, rendering a visual interaction floating layer with proper adaptive transparency and position on a video layer, and putting a digital advertisement to a user.

The invention discloses an AppStore application advertisement consumption estimation method and device, and the method specifically comprises the following steps: S1, carrying out the intelligent association of multi-source data, and extracting original data containing an application identifier, a keyword, a consumption value and a plurality of keyword feature indexes from a database; establishing data association, cleaning and filtering invalid data, and unifying data types to obtain a cleaned reference data set; s2, performing multi-dimensional feature engineering, and dividing the reference data set to obtain a training subset and a prediction subset; calculating a statistical value based on the training subset, performing missing value and abnormal value filling, numerical value conversion, statistical feature construction, interactive feature construction and feature screening on the training subset and the prediction subset, and generating a final feature matrix and a target variable; and S3, performing double-model fusion training. The invention relates to the technical field of digital advertisements, and particularly provides an AppStore application advertisement consumption estimation method and device.

A digital advertising system for a physical commercial location includes multiple digital displays positioned within store aisles, each display associated with a product category and / or a location zone context. A cloud-based server manages advertisement inventory and performance tracking. The server's auction module receives bids from advertisers and selects winning bids for each display based on its product category and / or location zone context. A performance tracking module applies an econometric attribution method to assign sales uplift to displayed advertisements and an action-based attribution method using tracked shopper actions. The system delivers context-sensitive advertising and provides robust attribution of ad performance within physical retail environments.

The invention discloses a decline identification method and device for e-commerce in-delivery materials, and relates to the technical field of digital advertisements. The method comprises the following steps: acquiring time sequence data of performance indexes of an input material in a preset time period; dividing the time sequence data of the performance indexes into a reference data segment corresponding to a first time window and a recent data segment corresponding to a second time window adjacent to the first time window; respectively constructing a reference geometric path and a recent geometric path based on the reference data segment and the recent data segment; calculating a reference path signature of the reference geometric path and a recent path signature of the recent geometric path; generating a change significance score based on a preset distance metric of the reference path signature and the recent path signature; and when the change significance score exceeds a preset decline threshold value, judging that the input material enters a decline state.