115 results about "Targeted advertising" patented technology

An AI-driven system for personalized advertising in real time, where: ◯ an analytics unit to monitor and analyze user behavior in real time across multiple digital platforms such as websites, mobile applications, social media, and smart devices; the unit collects data on user engagement, browsing patterns, time spent, and content preferences to enable targeted, personalized advertising; ◯ a prediction module that predicts preferences and interests of a user, operatively connected to the user interaction data collection unit, wherein the prediction module uses machine learning models such as deep learning, recurrent neural networks (RNNs) and transformer-based architectures to predict interests of users based on historical interactions and inferred preferences; ◯ an emotion and sentiment analysis unit that assesses the user's mood in real time through computer vision, natural language processing (NLP) and voice analysis, whereby the analysis of facial expressions, voice pitch and linguistic mood is used to determine emotional states and receptivity to advertising content; ◯ an embodiment of a context awareness component in operational communication with the emotion analysis and mood unit, in some cases further augmented by various environmental and situational data such as the device type and its physical location, date and time, and the content processed in the device, processing methods, etc., in establishing adaptability and automatic ad placement to be as relevant as possible to the user and their status as prescribed; ◯ Use reinforcement learning algorithms and generative AI models to drive advertising with personalization engines. Creative elements, messaging, and presentations are dynamically adjusted in real time based on user responses to ensure advertising is personalized and always optimized for best performance; o a privacy-focused AI system with federated learning, differential privacy methods, and on-device AI processing to reduce targeted advertising while complying with international data protection laws such as the General Data Protection Regulation (GDPR) and California consumer privacy laws; o an operationally adapted ad delivery mechanism to engage with real-time bidding (RTB) networks, programmatic advertising exchanges and demand-side platforms (DSPs) and place advertisements through digital advertising networks, which guarantees the delivery of tailored advertising to the most relevant audience in real time; and o a contextual feedback loop in which the machine learning models used in the preference and interest prediction module and in advertising personalization The engine is continuously updated to reflect the latest user engagement data, improving personalization over time and optimizing advertising performance.

The invention relates to an intelligent advertisement material automatic optimization method, system and device and a readable storage medium, and the method comprises the steps: receiving the real-time putting effect number of a target advertisement video; analyzing the target advertisement video through a pre-trained multi-modal analysis model, and generating a commodity display sequence, copywriting content and background music features in the advertisement video; associating the delivery effect data to the analyzed commodity display sequence, copywriting content and background music features, and inputting the data into a dynamic optimization decision engine to generate a three-element optimization instruction; and executing an automatic modification operation on the target advertisement video according to the three-element optimization instruction, generating an optimized advertisement video and putting the optimized advertisement video so as to realize the purposes of real-time analysis, accurate optimization and efficient putting of the advertisement video content and improvement of the user attraction and conversion effect of the advertisement.

The invention relates to the technical field of computers, and discloses a cross-region advertisement putting analysis and decision method and system based on artificial intelligence, and the method comprises the steps: responding to a cross-region advertisement putting instruction, carrying out the analysis of the cross-region advertisement putting instruction, and determining a target advertisement putting region in the cross-region advertisement putting instruction; obtaining multi-dimensional data of the target advertisement putting area; performing semantic analysis and code conversion on the multi-dimensional data, and constructing a structured regional data matrix; feature extraction is performed on the regional data matrix based on a preset deep learning algorithm, and potential features related to the advertisement putting effect are mined; and inputting the potential features into an advertisement putting decision model to obtain an advertisement putting strategy output by the advertisement putting decision model for the target advertisement putting area. According to the method, the problems that the dynamic change and potential trend of the market cannot be accurately predicted and the advertisement putting strategy is lack of accuracy are solved, and the accuracy and predictability of cross-region advertisement putting analysis decision are improved.

The invention provides a visual communication advertisement design system and method, and the method comprises the steps: carrying out the cross-modal feature alignment of a background voiceprint feature extracted from environment voiceprint data of an advertisement putting scene and a frequency domain feature of illumination intensity in illumination intensity data, and obtaining an environment perception state tensor; generating a dynamic illumination matrix by combining the spectral irradiance distribution in the environmental perception state tensor with the anisotropic highlight coefficient of each sub-region in the target advertisement picture; determining an audience space domain according to the space depth data of the advertisement putting scene and the audience motion trail, and performing space audio redirection on the target advertisement based on the audience space domain and the sound field energy distribution in the environment perception state tensor to obtain an acoustic beam width angle; and performing acousto-optic synchronous dynamic rendering on the advertisement content of the target advertisement according to the dynamic illumination matrix and the acoustic beam width angle. By adopting the scheme of the invention, acousto-optic collaborative rendering and acousto-optic parameter dynamic adaptation can be performed on the target advertisement so as to realize directional propagation to audiences.

A system for serving personalized advertisements based on biometric and identifying data captured by sensors. The system employs pre-processing, feature extraction, and recognition modules to identify individuals. A context-aware processing module adapts recognition strategies based on environmental data and analyzes personal information to confirm the identity of the targeted individual and send targeted advertisements. The system includes display and speaker modules for visual and audio advertisements, a predictive interaction modeling module for generating personalized advertisements, and a cross-platform behavior analysis module for analyzing user behavior across offline and online platforms.

The invention relates to the technical field of style migration, in particular to an advertisement design assisting method and system based on image style migration, and the method comprises the following steps: based on an input style image sample, analyzing the edge intensity characteristics of the image through calculating the brightness difference between a plurality of pixel points and neighborhood pixel points in the sample image, and obtaining the edge intensity characteristics of the image; in combination with analysis of texture modes and color distribution of images, a style feature data set is obtained by matching importance weights for various features. According to the method and the device, the style of the image sample is extracted, and the content of the processed image is extracted, so that the accuracy of style migration is improved, the style and the content of the target advertisement image are finely controlled, the definition and the conveying effect of the advertisement content are kept, and key visual features of continuous frame images are continuously monitored and adjusted; according to the method, the consistency of image styles among continuous frames is improved, and the consistency of the overall styles and the advertisement expressive force are ensured through analysis and adjustment of the style matching degree among a plurality of design elements.

A chatbot system detects commercial intent during conversations with users and provides targeted advertisements. The chatbot system extracts keyword candidates from a conversation and assigns relevance scores based on the meaning of the conversation and commercial scores based on a machine learning model trained to detect commercially-related keywords. The chatbot system selects keywords based on a combination of the scores and transmits the selected keywords to advertising content servers that provide advertising content including advertisements selected using the keywords. The chatbot system displays the advertisements to the user during the conversation. The chatbot system may integrate the advertisements into the chatbot's responses, select advertisements based on a predicted click-through rate for the user, train the machine learning model using translations of labeled examples, access a long-term memory of the user's conversations and user profile data to provide context for the advertisements, and analyze messages from multiple users in group chats.

Systems and methods for determining user intent and providing targeted advertisements using chat robot interactions are disclosed. The system receives user cues during a chat session with the chat robot and generates a response using a large language model. User intent is extracted by analyzing chat conversations using natural language processing and machine learning techniques. The extracted user intent including weighted keywords and concepts is used to create a user intent profile. Targeted advertising content is generated based on the user intent profile, and the targeted advertising content is provided to the user during subsequent platform interactions. The large language model is continuously retrained using the user participation data to improve intent modeling accuracy. User privacy is maintained by limiting context extraction to chat robot conversations. The system enables personalized and related advertising by inferring user intent via dialog interactions.

The invention relates to the technical field of directional advertisement, in particular to an advertisement putting method based on a user portrait, which comprises the following steps of: acquiring equipment use time of a target user, recording use types and corresponding use frequencies of software and corresponding advertisement response information, dividing the equipment use time into a plurality of putting characteristic time periods, determining the advertisement putting type of each putting characteristic time period; according to the advertisement feedback attitude of the user in each feature time period, determining an advertisement effective tendency category of the current user in each putting feature time period so as to determine a basic advertisement putting mode; and according to the duration percentage in each time period, determining an advertisement acceptance fluctuation parameter of the user in the current time period so as to judge whether to adjust the advertisement putting content in the current characteristic time period, and according to the advertisement watching duration percentage of each use type of software, determining an adjustment direction. And the overall advertisement putting effect is improved.

The invention discloses a directional advertisement putting system based on a rule engine, and belongs to the technical field of telecommunication networks. Through mutual cooperation and cooperation of an advertisement library management module, a user behavior construction module, an advertisement matching engine module, a flow reporting module and a real-time monitoring module, advertisement pre-putting information is processed based on a personalized label, and an advertisement is rapidly matched and selected when a terminal requests the advertisement. The problems of low efficiency and lack of flexibility caused by the fact that an existing advertisement delivery system is limited to a single terminal and a mechanical delivery mode are solved, consumed time and labor cost are reduced, advertisements are delivered more accurately according to labels, changes of consumer behaviors or changes of market trends can be responded in time, and the service life of the system is prolonged. And thus, the advertisement resource allocation accuracy and conversion rate are improved.

The invention relates to the field of advertisement creativity design, and discloses an advertisement creativity design method and system based on advertisement sample analysis, and the method comprises the steps: obtaining a plurality of competitive product video advertisements of a target product, key frame screenshots, forward comment time and forward comment keyword clouds of high-completion-rate fragments corresponding to the multiple competitive product video advertisements are obtained; clustering the plurality of competitive product video advertisements according to the key frame screenshots, the forward comment time and the forward comment keyword clouds of the high completion rate segments corresponding to the plurality of competitive product video advertisements to obtain a plurality of competitive product video advertisement categories, and determining a target competitive product video advertisement category in the plurality of competitive product video advertisement categories; and through the advertisement creativity design model, determining an advertisement creativity design scheme corresponding to the target product according to the plurality of competitive product video advertisements in the target competitive product video advertisement category. According to the method and the device, strategies, advantages and innovation points of competitors in the aspect of advertisement creativity can be automatically analyzed and designed in a targeted manner.

The invention discloses an advertisement putting control method, an advertisement putting system, a storage medium and a program product, and the advertisement putting method comprises the steps: receiving a business district image uploaded by a user based on a user terminal node, and then determining a group portrait corresponding to the business district according to the business district image; and then one or more advertisements most adaptive to the group portrait are selected from the advertisement library according to the group portrait as target advertisements, and target advertisement putting device nodes in the business district are controlled to play the target advertisements, so that the purpose of accurately putting the advertisements is realized, and a plurality of decentralization processes are realized. In this way, the advertisement putting income in unit time is effectively improved, and advertisement putting is more accurate. Moreover, by implementing the above scheme based on the block chain, the purpose of decentration is better achieved, and the problem of low advertisement putting efficiency caused by artificial interference is effectively avoided.

The invention discloses an advertisement directional pushing method based on video content, relates to the technical field of advertisement pushing, and solves the technical problem that target audiences really having demands cannot be effectively reached by fully considering personalized characteristics and demand differences of each user. According to the method, information such as browsing history records, search records and use time of the push users is obtained in detail, and scientific analysis methods such as time period division, classification of advertisements of the same type and frequency calculation are applied, so that a user portrait which is more accurate than that of a traditional mode can be constructed; therefore, advertisements meeting user requirements are pushed in a targeted mode, the matching degree of the advertisements and the users is improved, invalid advertisement putting is reduced, and by analyzing software use behaviors and advertisement browsing conditions of the users in different time segments, for example, the browsing ratio of different advertisement types and the software use frequency in the target time period are calculated, so that the user experience is improved. And the advertisement pushing times and types are reasonably adjusted.

A method for selecting and inserting contextually relevant advertisements into a video stream, executed by a processing system in a network server computing device, encompasses receiving a primary video stream with potential advertisement insertion points indicated by SCTE35 / SCTE104 markers, extracting an audio segment from this stream before an advertisement break, obtaining audio from potential advertisements, transcribing both primary and secondary audio segments into textual data, performing semantic analysis and tokenization on this data, creating vector embeddings, and normalizing these embeddings for a feed-forward neural network. The method further involves determining semantic similarity scores between the primary and secondary content through a transformer-based AI model, generating a similarity matrix from these scores, identifying the most contextually aligned advertisement based on these scores, and inserting this advertisement at an indicated break point in the primary video stream.

A system includes a phased array antenna, a signal processing module configured to detect wireless signals received from one or more target devices, a conversion module configured to determine 3D spatial data for the one or more target devices based on the wireless signals, an integration module configured to receive visual data from at least one camera, perform object detection and classification on the visual data to detect and classify one or more objects, and tag the one or more objects with 3D coordinates based on the 3D spatial data for the one or more target devices; and a correlation module configured to synchronize the 3D spatial data from the conversion module with the visual data from the integration module including object detection and classification information for use in a cloud-based augmented reality (AR) content to augment social networking and targeted advertising.

A system for providing targeted advertisement based on user profile and location [0027] The invention relates to a system (100) for providing targeted advertisement based on user profile and location. The system (100) comprises a web server (101) for providing browsing insights associated with one or more users over a communication network (105), wherein the users belong to one family. Further, the system (100) comprises a location determination unit (102) for providing location information of the users. Furthermore, the system (100) is configured to analyze the browsing insights and location information associated with the users, predict the age of the users based on the browsing insights, establish a user profile and corelate with the relevant location, and select and provide one or more targeted advertisements from among candidate advertisements to the user.

This invention discloses an intelligent advertising design and generation method, specifically including the following steps: S1, Data Collection and Preprocessing: Collecting product data, user behavior data, historical advertising data, and real-time market data, and performing cleaning, labeling, and feature extraction; S2, User Profile Modeling: Constructing a dynamically updated user interest graph based on clustering analysis and deep learning algorithms; This invention relates to the field of artificial intelligence technology. This intelligent advertising design and generation method integrates multi-dimensional data such as product functions, user behavior, and competitor dynamics to improve the accuracy of advertising content, generate targeted advertising copy, support the joint generation and style unification of text, images, and videos, and the system can simultaneously generate advertising slogans such as "Riding the Wind, Unlocking the Acceleration of Youth" and dynamic posters, track click-through rates, conversion rates, and other indicators in real time, automatically adjust content parameters, use blockchain technology to store copyright information, and protect user data through differential privacy algorithms.

An advertising campaign may be carried out using moving outdoor advertising. Advertisers typically like to manage and track the success of their advertising campaigns. Aspects of the present application may be seen to assist with such management and tracking by providing impression analytics, location analytics, time analytics and frequency reports. Furthermore, aspects of the present application may be seen to provide an ability to augment a moving outdoor advertising campaign with a mobile device retargeting advertising campaign. Then, such metrics as return on investment, profit and gross profit may be tracked. In some aspects, Wi-Fi signals and Bluetooth signals may be collected from mobile devices that are in the range of a Moving Impression Analytics Tracking Device.

Disclosed is a system for calculating the potential for a player who is playing a game to leave the game by using an artificial intelligence algorithm. Training data includes play data which is data related to the play history for the game of the player, player information which is information about the personal characteristics of the player, and game data which is data representing the characteristics of the game. In addition, for supervised learning of an artificial intelligence algorithm, leave result data, which is data of an actual result of the player's leaving the game, is used for the learning. The potential for leaving is determined on the basis of a prescribed elapsed time from the final time point at which the player actually played the game. The advertising effectiveness can be increased by performing a targeted advertising for a player determined to have a high potential of leaving.

The invention discloses an offline advertisement intelligent putting system based on big data and AI, and relates to the technical field of directional advertisement optimization, and the system comprises a causal decision module which constructs a dynamic causal map based on a panoramic situation data flow, carries out the intervention effect analysis, and generates a quantum decision vector; the quantum coding module is used for executing quantum state probability amplitude mapping and entanglement particle binding on the quantum decision vector to generate a quantum decision proposal packet; the collaborative optimization module is used for constructing a global quantum entangled state model, carrying out conflict resolution optimization on the quantum decision proposal package and generating a quantum collaborative execution instruction; and the report generation module is used for executing quantum state collapse operation on the quantum cooperative execution instruction and generating an intelligent putting report. According to the invention, by constructing the dynamic causal atlas and quantum collaborative architecture, normal form upgrading of advertisement decision from correlation analysis to causal intervention is realized, so that the system has the capability of accurately quantifying the real effect of advertisement action and millisecond-level dynamic response.

The invention discloses a table display method and device for an advertisement screen, electronic equipment and a storage medium. The method comprises the following steps: in response to an advertisement screen connection operation, connecting a target advertisement screen; and in response to a table editing operation, creating an initial table, and performing style editing on the initial table to obtain a target table of a dynamic style, in response to a storage preview operation, generating a code file corresponding to the target table, and displaying the target table of the dynamic style based on the code file; in response to a table release operation, compressing the code file to obtain a compressed file, and sending the compressed file to the target advertisement screen; and the target advertisement screen displays the target table of the dynamic style based on the compressed file. Based on the technical scheme, the table display efficiency of the advertisement screen can be effectively improved.

The invention discloses an advertisement attribution method and device. In the scheme, in response to a target application package installed by a user, installation information and an attribution strategy of the target application package are acquired; and matching target advertisement contact data from a target database based on the installation information. And configuring a target advertisement attribution model based on the attribution strategy. And inputting the target advertisement contact data into the target advertisement attribution model to obtain an advertisement attribution result. According to the scheme, the target database is utilized to associate the advertisement contact data in the time dimension, and the target advertisement attribution model flexibly configured based on the attribution strategy is combined, so that the customized configuration of the advertisement attribution model is realized, and the accuracy of advertisement attribution is remarkably improved in the face of complex and changeable advertisement putting scenes.

The invention is suitable for the field of data processing, and provides an advertising language correction method and device based on a large language model, equipment and a storage medium. Multi-language advertising language data and target area culture rule data are obtained, emotion vectors are generated through analysis, and culture metaphor features are extracted through comparative learning; accurate capture of advertising language emotion and cultural semantics in a cross-cultural context is realized; a culture sensitivity index is calculated in combination with a culture and emotion mapping library to generate a compliant alternative scheme, and a target advertising language with culture adaptability and marketing conversion potential is screened through a conversion rate prediction model; the problems that in a traditional method, emotion misjudgment is prone to occurring in cross-culture advertising words, the culture compliance risk is high, and the marketing conversion effect is difficult to consider are effectively solved, the corrected target advertising words can meet the target area culture rule, audience emotion cognition and marketing conversion requirements at the same time, and the effectiveness of cross-culture advertising is improved.

Disclosed is The invention discloses a system and method for integrating terrestrial TV and Pay TV broadcasts into an Over-The-Top (OTT) platform using QR Codes. Through real-time QR Code generation containing encrypted URLs, users can instantly access streaming content, digital versions, and supporting materials via smart devices. Such a system may enhance interactivity, may enable monetization through targeted advertisements and premium content, and is equipped with security features, user analytics, and validation mechanisms to ensure reliability and scalability.

To provide an Artificial Intelligence Internet Of Things (AIOT) system capable of performing appropriate management of a breeding environment and support of decision-making in a breed-specific data base farm.SOLUTION: An AIOT system 100 includes at least one smart buoy 111 that periodically collects and provides breeding environment data in a farm using at least one or more built-in sensors and functions as an edge server in an AIOT system; a main server 130 that provides, on the basis of the breeding environment data in the farm received by a smart buoy using artificial intelligence and meteorological and marine information data provided by a relevant agency, recommended environmental data for species bred in the farm and provides decision support required to build the recommended environment data and targeted advertising of necessary consumables; and a user terminal 120 that performs a customization operation related to the recommended environmental data and purchases the consumables using the targeted advertising.SELECTED DRAWING: Figure 1

Topics of potential interest to a user, useful for purposes such as targeted advertising and product recommendations, can be extracted from voice content produced by a user. A computing device can capture voice content, such as when a user speaks into or near the device. One or more sniffer algorithms or processes can attempt to identify trigger words in the voice content, which can indicate a level of interest of the user. For each identified potential trigger word, the device can capture adjacent audio that can be analyzed, on the device or remotely, to attempt to determine one or more keywords associated with that trigger word. The identified keywords can be stored and / or transmitted to an appropriate location accessible to entities such as advertisers or content providers who can use the keywords to attempt to select or customize content that is likely relevant to the user.

This application relates to a method, apparatus, device, and medium for generating advertising text in the field of computer technology. The method includes: acquiring the title of an advertised product and its reference advertising text; using a text generation model's encoder-decoder network to decode the title time-step by time to obtain decoded feature information, and determining its generation probability distribution mapped to a first reference vocabulary referenced by the encoder-decoder network; using a text generation model's encoder to obtain encoded feature information of the comprehensive text composed of the product title and its reference advertising text, and determining its key feature information relative to the decoded feature information as a pointer probability distribution; calculating and determining a matching weight based on the encoded feature information and the decoded feature information, and smoothly weighting the generation probability distribution and the pointer probability distribution with the matching weight to obtain an optimized probability distribution; and determining the lexical units of the target advertising text based on their word selection in the first reference vocabulary or the comprehensive text. This application can generate high-quality advertising text.

Data characterizing historical skills-based gaming metrics for a first user and historical skills-based gaming metrics for at least one second user is accessed. Using the accessed data and a set of rules, a targeted advertisement to present to the first user is determined. The targeted advertisement specifies at least one skills-based game and a characterization of the at least one second user's historical skills-based gaming metrics. The targeted advertisement is generated. Data characterizing the targeted advertisement is provided. Related apparatus, systems, techniques, and articles are also described.