46 results about "Computational advertising" patented technology

The invention discloses a short video advertisement putting optimization evaluation method based on deep learning, and relates to the technical field of advertisement putting, and the method collects user behavior data in real time, constructs a dynamic user portrait, enables an advertisement system to adjust the advertisement content and putting strategy in time according to the interest change of a user, improves the correlation of advertisements, and improves the advertisement putting efficiency. Meanwhile, user behavior mode data and advertisement content labels are subjected to multi-dimensional matching, and the matching degree of the advertisements and user interests is calculated by combining cosine similarity with a weighting algorithm, so that advertisement recommendation is more personalized and accurate, the advertisement click rate and conversion rate are greatly improved, and the advertisement recommendation efficiency is improved. Meanwhile, the optimal opportunity of advertisement display is defined by analyzing the exit tendency of the user and the advertisement clicking tendency, it is guaranteed that the advertisement can be displayed at the moment when the user is most likely to interact and click, and the problem of low conversion rate caused by poor opportunity in a traditional method is solved.

The invention provides an intelligent optimization advertisement putting method, which belongs to the technical field of advertisement putting channel strategies, and is characterized in that interaction between users and advertisements is enhanced through multi-dimensional user feature extraction, double-tower model matching and a multi-head self-attention mechanism, advertisement matching scores are accurately calculated, and contribution of the advertisements to GMV is evaluated in combination with a multi-contact attribution model; the advertisement conversion rate is predicted through a logistic regression dichotomy model, the payment capacity of a user is evaluated in combination with a user lifetime value model, and an ROI prediction model is constructed to optimize advertisement budget allocation; the advertisement effect and the ROI are monitored in real time, the putting strategy is dynamically adjusted, and high efficiency and sustainability of advertisement putting are ensured. According to the method, accurate user matching, efficient cost control and global optimization are realized, the return on investment of advertisers and the long-term value of the users are improved, the flexibility and adaptability of advertisement putting are ensured, and a transparent and explainable putting solution is provided for the advertisers.

The invention provides an elevator multi-mode crowd feature perception and intelligent advertisement putting method and system, and relates to the technical field of intelligent advertisement putting, and the method comprises the steps: collecting multi-mode perception data in an elevator through an edge computing terminal; performing feature decoupling on the data, performing cross-modal semantic alignment, establishing a directed association relationship between modals, and constructing a scene feature map; calculating the topology importance degree of map nodes, screening feature nodes, and extracting context information for semantic coding; mapping the scene semantic code and the advertisement audience semantic code to a two-dimensional coordinate system to construct a semantic matching graph, and extracting an optimal matching path to form a candidate set; predicting a scene evolution trend based on the scene characteristic spectrum evolution trajectory, and calculating an advertisement adaptive score to generate a playing sequence; putting and collecting user interaction data feedback according to the sequence to update the graph structure. According to the invention, accurate crowd feature recognition and advertisement dynamic matching are realized, and the advertisement putting efficiency and the user experience are improved.

The invention belongs to the field of advertisement analysis, and provides an advertisement putting effect evaluation and analysis system and method based on data analysis, and the method comprises the steps: constructing a cognitive state vector of a user based on multi-source behavior data before and after the contact between the user and an advertisement; modeling is conducted on user cognitive state vector changes caused by advertisement putting, cognitive intervention vectors of the advertisements are generated, and the cognitive intervention vectors represent the variable quantity of the cognitive states of the users after the users make contact with the advertisements; based on the language feedback, the visual behavior and the emotion track of the user, evaluating the consistency between the user behavior response and the cognitive intervention vector direction, and outputting a multi-modal behavior consistency score; tracking a behavior path of the user from advertisement click to final conversion, forming a conversion chain feature, and identifying a path length, a path node type and a path response time delay; and fusing the cognitive intervention vector, the multi-modal behavior consistency score and the conversion chain feature, and calculating a cognitive effect comprehensive score of advertisement putting for putting effect evaluation.

The invention discloses a cross-border advertisement accurate delivery method, system and device based on a user portrait, relates to the technical field of cross-border digital marketing, and discloses the cross-border advertisement accurate delivery method, system and device based on the user portrait, which generates an accurate user portrait by integrating cross-regional behavior data. An advertisement putting strategy is dynamically calculated in combination with exchange rate, tax and logistics economic parameters, and compliance adaptation is performed based on legal and cultural rules, so that the problems of single data dimension, inaccurate user portraits and lack of economic variables in the prior art are solved; the method has the advantages that the cross-border advertisement putting accuracy and conversion effect are improved, and the compliance risk is reduced.

The invention relates to a dynamic advertisement putting method and system oriented to a large language model, and belongs to the technical field of generative artificial intelligence and calculation advertisement crossing. According to the method, the semantic splitting problem of advertisements and natural language streams is solved through a three-level collaborative architecture, firstly, a semantic depth alignment module is constructed, and advertisement and natural language vectors are projected to a unified semantic space by using dual-channel adversarial training and orthogonal mapping constraints; a dynamic context adaptation module is constructed, dominant intentions are analyzed based on a self-attention mechanism, and scene advertisements are generated by fusing space-time-equipment signals; and finally, constructing an anti-fragility regulation and control module, and dynamically balancing the advertisement density and the user experience through an exponential attenuation model and a reinforcement learning fusing mechanism. The method breaks through the limitation of a static advertisement template, realizes the adaptive fusion of the advertisement content and the generative interaction scene, and is suitable for scenes such as a multi-language dialogue system and an intelligent search engine.

The invention discloses a new media promotion method and system based on the Internet, and belongs to the technical field of new media promotion, and the method specifically comprises the steps that the distribution density and the stop position of people in a waiting area are monitored in real time, load distribution data in a lift car are collected, and the vibration frequency and the start-stop state in the elevator running process are recorded; when it is detected that the density of people in the waiting area exceeds a set threshold value, switching to duration compressed advertisement content, and when the load distribution of the lift car displays that one side is crowded, displaying interactive advertisements in the free area; capturing a user eyeball movement track, calculating an advertisement interface fixation thermodynamic diagram, identifying a user gesture operation by using a millimeter wave radar, mapping a specific gesture into an advertisement content switching instruction, and generating a personalized advertisement recommendation scheme; and the advertisement interaction data is converted into a pushing strategy adjustment basis of adjacent elevators, a propagation path is established according to the flow rule of people in the elevator room, and when the advertisement click rate of a certain elevator exceeds a set value, a content recommendation signal is sent to the associated elevator.

The invention aims to provide a social network advertisement propagation and user behavior analysis integrated system, which belongs to the technical field of marketing data analysis and comprises a data acquisition module, a user portrait module, a propagation path module, a prediction engine module and an optimization regulation module. The data acquisition module acquires social data, advertisement interaction data and user behavior data. The user portrait module constructs a social influence model and generates a user feature tag and an interest map. The propagation path module identifies key propagation nodes, constructs a social network propagation model, and generates network diffusion vectors. The prediction engine module establishes a prediction model, calculates an advertisement interaction probability index, generates a resource allocation and optimal push strategy, generates a performance evaluation signal, and is bidirectionally connected with the optimization regulation and control module. The optimization regulation and control module monitors and predicts the operation state of the engine module in real time and sends out an optimization instruction according to the performance evaluation signal. The system can accurately analyze the user behavior, predict the advertisement propagation path, optimize the advertisement putting effect and improve the advertisement interaction possibility.

The embodiment of the invention provides a display device and an advertisement data playing method. According to the method, storage positions are dynamically allocated according to advertisement data characteristics, memory occupation is reduced, and the access speed of key data is increased; a priority score is generated by calculating the access frequency, the resource type weight and the final access time of the advertisement data, and a low-score data block is preferentially removed when the storage space is insufficient, so that the cache hit rate of high-frequency / hot advertisements is ensured; by downloading recent advertisement data to the local in advance, real-time downloading delay during playing is avoided, large file advertisements are stored in blocks, cached parts are read preferentially during playing, meanwhile, remaining data blocks are downloaded in the background, and rapid playing of the advertisement data is achieved. In addition, cloud advertisement data change is monitored, local cache is dynamically synchronized, data timeliness is ensured, a local index table is quickly queried before the advertisement is played, direct playing or playing while playing is selected according to cache integrity, waiting time is shortened, and the problem that the advertisement playing speed is low is solved.

The invention discloses an advertisement putting effect optimization method combining user groups and pre-putting, and relates to the technical field of advertisement calculation, and the method comprises the steps: obtaining a user behavior data stream in real time, detecting the user feature distribution drift through a Wasserstein distance, triggering an adversarial generative network to dynamically divide the user groups when the drift exceeds a drift judgment threshold, and obtaining a user behavior data stream; outputting a user group label and a user-group membership matrix; and collecting real-time conversion data after execution of the multi-objective optimization strategy, evaluating a user group offset degree and an anti-fact prediction error through a mahalanobis distance, and triggering grouping model reconstruction and causal model calibration. Through closed-loop optimization of dynamic grouping, anti-fact gain calculation, multi-target strategy cooperation and feedback calibration, the advertisement resource utilization rate and conversion rate are continuously improved, the user fatigue is effectively reduced, and the strategy iteration period is shortened to the minute level.

The invention relates to an advertisement click-through rate prediction method and prediction system based on multi-scale feature fusion. The method comprises the following steps: analyzing a feature tag of an advertisement object; matching a reference advertisement object with the advertisement object by using the feature tag; calculating a predicted click rate of the advertisement object and comparing the predicted click rate with an actual click rate of the reference advertisement object to obtain a comparison result; calculating the error degree of the comparison result, replacing the reference advertisement object according to the error degree, and repeatedly calculating the comparison result; drawing a comparison result curve by using the comparison result and the comparison result ranking; and using the last comparison result in the sequential sequence as the predicted click rate of the advertisement object. According to the advertisement click-through rate prediction method and prediction system based on multi-scale feature fusion disclosed by the invention, the advertisement click-through rate is calculated by using a reference mode, and the reference content is corrected according to the calculation result, so that a more accurate reference sample can be obtained, and more accurate click-through rate data can be obtained based on the reference sample.

The embodiment of the invention provides a computing advertisement creative agent construction method and related equipment, and belongs to the cross technical field of artificial intelligence and computing advertisement. The method comprises the following steps: sensing behaviors, environments and intentions of customers in real time through multi-modal data, and constructing dynamically updated scene semantic digital twins; based on the difference between the digital twinborn feedback and the expectation of the advertiser, disassembling a creative generation task into sub-tasks by using an RPA technology; and retrieving materials from the creative knowledge base by adopting a learning-decision-modeling-prediction (LDMP) model in combination with a retrieval enhancement generation (RAG) technology, and performing effect estimation and iterative optimization on the generated new creativity in a digital twin simulation environment until the personalized advertisement creativity meeting the expectation is output. Through deep fusion of digital twinning, RPA and generative AI, high intelligence, automation and individuation of advertisement creative generation are realized, and the advertisement putting effect and the user experience are remarkably improved.

The invention relates to the technical field of advertisement data analysis, in particular to a mobile advertisement effect analysis method and system based on user behaviors. According to the method, detailed data of user behaviors and advertisement putting are captured in real time through an SDA interface and an API interface of a mobile advertisement platform, users are subdivided into user groups with different activeness, activeness and consumption levels by calculating activeness parameters, advertisement activeness parameters and consumption level parameters, accurate description and classification of the user behaviors are achieved, and the user experience is improved. The method helps advertisers to more accurately position target users, can mine potential user demands, improves the precision and conversion rate of advertisements, and reduces the cost of the advertisements at the same time. The advertisement putting effect is comprehensively evaluated by calculating key indexes such as the advertisement revenue index, the advertisement adaptation degree index and the shopping willingness index, a scientific decision basis is provided for advertisers, the advertisement putting strategy is optimized, and the advertisement effect is improved.

The invention relates to the field of advertisement putting, and discloses a cross-platform dynamic advertisement promotion strategy intelligent generation system and method, and the system comprises a data collection module which is used for collecting original data from an advertisement platform, and carrying out the cleaning, processing and storage of the collected original data; the optimization engine module is used for constructing an advertisement putting strategy by applying a preset multi-objective optimization algorithm based on the cleaned original data, and calculating the optimal allocation of advertisement resources among the advertisement platforms by utilizing a game theory model; and the dynamic adjustment module is used for dynamically adjusting an advertisement putting strategy in real time according to the user behavior data and the advertisement putting data based on a Markov decision process model. According to the invention, by introducing the multi-objective optimization algorithm, the game theory model and the dynamic adjustment mechanism, accurate configuration and real-time optimization of cross-platform advertisement resources are realized, and the advertisement putting effect and the resource utilization efficiency are improved.

The invention provides a banner advertisement putting method and device, and the method comprises the steps: collecting user behavior data through a rear-end point burying method, and constructing a user preference matrix with a potential factor model; constructing an interaction matrix according to the user preference matrix and the advertisement matrix; for each user in the interaction matrix, screening high-score advertisements according to preference degree values; obtaining user feature data from the server to calculate average reading time corresponding to the advertisement display page in each preset time period; and determining a banner advertisement putting duration corresponding to each preset time period according to the high-score advertisement and the average reading time, and putting the banner advertisement. The putting duration of the banner advertisement is dynamically adjusted according to the user behavior data and the user feature data, invalid display is avoided, and the user experience is improved. Meanwhile, in consideration of user behavior differences in different time periods, the putting duration of the banner advertisement is also optimized, the adaptability and flexibility of the system are enhanced, the user loss is effectively reduced, and the participation degree and the activeness are improved.

The invention relates to the technical field of internet advertisement services, and particularly discloses an intelligent advertisement pushing method based on an internet advertisement platform, which comprises the following steps: S1, taking the time when a user logs in the platform as a starting point, obtaining the stay duration of the user, and calculating the attention value of the user; s2, obtaining the advertisement pushing times of the platform in the monitoring period, and calculating the quality of the advertisement; s3, obtaining the number of times that the advertisement watching duration of the user is smaller than a preset value, correcting the quality to obtain comprehensive quality, calculating the mean value of the comprehensive quality of the advertisement, and setting an initial coefficient of the advertisement; and S4, setting an initial attenuation factor based on the comprehensive quality and the mean value, sorting and pushing the advertisements, updating the initial coefficient of the advertisements, and re-sorting and pushing the advertisements. Advertisement pushing is carried out on the user in a polling mode, the current situation that a head platform monopolizes flow and data is reduced, small and medium-sized enterprises obtain fair display opportunities, the Mortai effect is weakened, and innovation vitality is improved.

This invention discloses an optimization method combining user groups and pre-deployment advertising effectiveness, belonging to the field of computational advertising technology. The method includes: real-time acquisition of user behavior data streams; detection of user feature distribution drift using Wasserstein distance; triggering an adversarial generative network to dynamically segment user groups when a drift threshold is exceeded; and outputting user group labels and user-group membership matrices. It also involves collecting real-time conversion data after the execution of a multi-objective optimization strategy, evaluating the degree of user group shift and counterfactual prediction error using Mahalanobis distance, and triggering cluster model reconstruction and causal model calibration. This invention achieves continuous improvement in advertising resource utilization and conversion rate through closed-loop optimization of dynamic clustering, counterfactual gain calculation, multi-objective strategy collaboration, and feedback calibration, effectively reducing user fatigue and shortening the strategy iteration cycle to the minute level.

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.

The invention relates to the technical field of financial marketing, in particular to an integrated financial marketing management method and system based on a marketing data domain, and the method comprises the following steps: collecting customer transaction and preference data, calculating a change amplitude, normalizing the change amplitude into a feature vector, analyzing a group difference degree, calculating a change rate, and generating a judgment result; a personalized marketing plan is generated by combining the life cycle data clustering stage number and the conversion progress matching rhythm parameter, the advertisement space pushing frequency and the consultant service proportion are calculated according to the multi-group requirement to carry out resource optimization distribution, and interaction and transaction data after resource scheduling are collected and input into a regression model to be analyzed to generate a marketing effect evaluation result. According to the method, customer transaction and preference data quantitative changes are collected and normalized into feature vectors, a group difference degree dynamic identification state is analyzed, a life cycle clustering matching rhythm parameter generation strategy is combined, the advertisement space pushing frequency and consultant service proportion is optimized according to group requirements, and regression analysis is carried out to form closed-loop optimization management.

To provide an information processing device, a computation method and a program, which enable more appropriate computation of advertising fees.SOLUTION: An information processing device is provided, comprising a computation unit configured to compute a reward to be paid to a user when advertisement information attached to an item held by an avatar of a user is viewed by other users and link information to the item is manipulated.SELECTED DRAWING: Figure 1

This invention provides an information processing method, system, and program that enable the analysis of advertising effectiveness. [Solution] The method obtains first time series data, which is time series data of calculation period KPIs related to advertising a product or service, and the delivery time of the advertisement. It creates second time series data by omitting the calculation period KPIs within a predetermined time after the advertisement delivery time from the first time series data. Based on the second time series data and first reference information, it estimates third time series data by interpolating the missing portion. The first reference information is information that shows the relationship between the time series data before interpolation and the time series data after interpolation. The method also calculates a confidence interval in the third time series data based on the third time series data and the second reference information. The second reference information is information that shows the relationship between the time series data and the confidence interval. The method further calculates the advertising effect based on the confidence interval and the calculation period KPIs, and generates display information regarding the advertising effect.

The accuracy of impact measurement related to advertisements delivered to user terminals will be improved. The advertising apparatus includes: a storage unit that stores first user identification information and purchasing behavior information regarding a user identified by the first user identification information, the first user identification information and purchasing behavior information being related to each other; a unit that sends advertisements related to predetermined products or services to a plurality of user terminals, by determining different second user identification information for each user terminal; a unit that identifies the first user identification information that matches the second user identification information by comparing the first user identification information with the second user identification information;and a unit that calculates reaction information to an advertisement that indicates how many users have purchased a predetermined product or service among users identified by the first matched user identification information, based on purchase history information regarding the predetermined product or service, the purchase history information being included in the purchase behavior information associated with the first matched user identification information.;

The application discloses a cross-border advertisement accurate delivery method, system and device based on user portrait, relates to the technical field of cross-border digital marketing, and discloses the cross-border advertisement accurate delivery method, system and device based on user portrait, which generates accurate user portrait by integrating cross-regional behavior data, dynamically calculates an advertisement delivery strategy in combination with exchange rate, customs duty and logistics economic parameters, and is adapted in compliance with laws and cultural rules, thereby solving the problems of single data dimension, inaccurate user portrait and missing economic variables in the prior art, and having the advantages of improving cross-border advertisement delivery accuracy, conversion effect and reducing compliance risks.

The application belongs to the field of internet advertisement service, and provides a short video advertisement recommendation method, which comprises the following steps: capturing real-time interaction data of a user; obtaining a user label according to the real-time interaction data of the user; obtaining an advertisement sequence according to the user label, and calculating a real-time concurrent performance index of the advertisement; generating an optimal advertisement sequence combination according to the real-time concurrent performance index, and performing advertisement recommendation according to the optimal advertisement sequence combination. According to the advertisement recommendation method of the embodiment of the application, the timeliness and concurrent load of the advertisement can be comprehensively evaluated, the effect and efficiency of advertisement delivery are improved, the stability and user experience of digital content multi-network channels are enhanced, and the advertisement delivery process is comprehensively optimized.

The invention belongs to the field of internet advertisement services, and provides a short video advertisement recommendation method, which comprises the following steps of: capturing real-time interaction data of a user; obtaining a user tag according to the user real-time interaction data; obtaining an advertisement sequence according to the user label, and calculating an advertisement real-time concurrence efficiency index; and generating an optimal advertisement sequence combination according to the real-time concurrent efficiency index, and performing advertisement recommendation according to the optimal advertisement sequence combination. According to the advertisement recommendation method provided by the embodiment of the invention, the timeliness and the concurrent load of the advertisement can be comprehensively evaluated, so that the advertisement putting effect and efficiency are improved, the stability of a digital content multi-network channel and the user experience are enhanced, and the advertisement putting process is comprehensively optimized.

An information processing apparatus, a calculation method, and a program for more appropriately calculating an advertisement rate are provided. The information processing apparatus includes a calculation unit that calculates a reward to be paid to a user on the basis of a fact that advertisement information attached to an item carried by an avatar of the user has been visually recognized by another user and a fact that there has been an operation on link information related to the item.

To provide an information analysis device, an information analysis system, an information analysis method, and an information analysis program that can efficiently collect data necessary for performing analysis based on information related to advertising expenses, such as calculating advertising effectiveness indicators, in particular collecting information related to advertising expenses.SOLUTION: Provided is an information analysis device for performing analysis related to advertising based on advertising expense information related to advertising expenses, comprising: an advertising expense information acquisition unit for acquiring the advertising expense information from an advertising-related apparatus in which the advertising expense information is accumulated; an achievement information acquisition unit for acquiring achievement information indicating achievements related to a target to be advertised corresponding to the advertising expense information; an information storage unit for storing the advertising expense information acquired by the advertising expense information acquisition unit and the achievement information acquired by the achievement information acquisition unit; and an analysis unit for performing the analysis using the advertising expense information and achievement information stored in the information storage unit.SELECTED DRAWING: Figure 1

The invention relates to the technical field of computer service platforms, and discloses a computer service platform for advertisement recommendation, which comprises a data acquisition module, an analysis module, a platform recommendation module, an evaluation module and a comprehensive feedback module, the analysis module calculates a user characteristic index, an environment characteristic index and a comprehensive influence index according to the data acquired by the data acquisition module, and the platform recommendation module calculates an advertisement matching degree with platform advertisements according to the user characteristic index, the environment characteristic index and the comprehensive influence index; an evaluation module calculates an advertisement recommendation effect, a user feedback index and a recommendation comprehensive index, and a comprehensive feedback module generates a report for advertisement recommendation feedback according to the recommendation comprehensive index, so that the requirements and preferences of the user are accurately grasped, and the advertisement more conforming to the interest is recommended; and the advertisement recommendation effect is improved.

To support an advertising strategy by analyzing correlation by using data such as sales held by a facility operator and visitors' behavior data, and calculating investment effectiveness for the arrangement of advertisements on the basis of a result of the analysis.SOLUTION: An advertisement support device is provided, comprising: a movement data generation unit that automatically generates movement data from human flow data of consumers; a staying data generation unit that automatically generates staying data of visitors to a facility from the movement data or traffic data; a sales promotion target importance calculation unit that determines the importance of a sales promotion target attribute (sales promotion target importance) in an advertisement source facility by using the visitor staying data and facility data of the advertisement source facility; an advertisement investment effectiveness calculation unit that calculates the investment effectiveness of the advertisement by using the sales promotion target importance, advertisement source staying data, and advertisement source candidate data; a budget allotment calculation unit that allots an advertisement budge on the basis of the investment effectiveness; and a display screen creation unit that displays a result of calculation of the budget allotment on a terminal device.SELECTED DRAWING: Figure 2

The invention discloses a vehicle-mounted intelligent networking advertisement release and display method and system, and relates to the technical field of advertisement release and display, and the method comprises the steps: enabling an advertiser to carry out the advertisement release through constructing a cloud vehicle-mounted advertisement release platform, and setting an advertisement display scheme according to the vehicle owner information, the vehicle owner and advertisement interaction record and scene data, constructing a vehicle-mounted advertisement feature vector; carrying out group classification on the vehicle owners by adopting a clustering analysis algorithm to obtain a grouping result of a vehicle owner group; constructing an advertisement transaction item set of the vehicle owner group through an association rule learning algorithm, and generating a plurality of frequent transaction items by calculating the support degree of each single transaction in the advertisement transaction item set; and generating a group specific advertisement matching rule set, screening and matching candidate group specific advertisement matching rules to generate a preferred push advertisement, and pushing the advertisement to the vehicle owner. According to the method, intelligent matching and personalized recommendation of the advertisement content are realized through a double-layer optimization mechanism of clustering analysis and association rule learning.