571 results about "Content distribution" patented technology

The invention discloses a media content production and distribution integrated system based on multi-agent collaboration, and relates to the technical field of media content production and distribution. The system comprises a content creation multi-task intelligent system, an audience analysis multi-task intelligent system and a media content distribution module, and the content creation multi-task intelligent system comprises a topic selection planning agent, a text creation agent, an article illustration agent and a content evaluation agent. The audience analysis multi-task intelligent system comprises a data processing agent, a user portrait agent and an interest prediction agent, and through functions and cooperation of the agents, an AI large language model and a multi-agent cooperation technology can be introduced, so that a full-service process from media content production to media content distribution can be automatically opened, and the efficiency is improved. And automatic production and personalized distribution of the media content are realized, the production efficiency and the propagation effect of the media content are greatly improved, and practical application and popularization are facilitated.

Aspects of the present disclosure may include systems and methods generating visual content. The system may detect input of descriptive text associated with text content or audio content. The system may generate, based on the descriptive text, an initial latent representation by using a finetuned latent diffusion model. The system may apply a denoising process to the initial latent representation to produce a refined latent representation. The system may sample data points from a content distribution associated with prior timesteps and from a style distribution associated with subsequent timesteps, thereby generating a final image latent. The system may decode the final image latent to obtain a visually aligned image(s) corresponding to the descriptive text. The system may output the visually aligned image(s) on a user interface or a display.

The invention discloses a scheduling system of a content distribution network based on edge computing, and relates to the technical field of computer networks. An edge resource sensing module; an NLP semantic analysis module; reinforcing a learning scheduling engine; a semantic and resource linkage module; and a federation collaboration module. According to the scheduling system of the content distribution network based on edge computing, semantic understanding is carried out on a request of a user to analyze a deep intention of the user, edge node multi-dimensional state sensing data and a semantic label vector are integrated, a scheduling action is generated based on a node state and the user intention, and the scheduling effect is improved. Therefore, each edge node is fully utilized while user requirements are met, the edge nodes have caching, computing and scheduling capabilities, the limitation of surface feature matching of a traditional CDN is broken through, technical upgrading from traditional file type recognition to intention understanding and from a fixed rule to dynamic intelligence is realized, and finally, the resource efficiency and service quality of the CDN are improved.

The invention discloses a hierarchical traffic prediction-based multi-terminal video display adaptive method, which comprises the following steps of: acquiring network traffic, user behaviors and equipment state information in real time by constructing a multi-dimensional feature acquisition module, and generating a dynamic feature matrix containing traffic, interaction and performance features; processing the feature matrix by using a deep learning model, and generating and dynamically adjusting a network traffic grading prediction result; formulating an optimized video content distribution strategy based on a prediction result and equipment performance parameters, and coordinating multi-terminal resource distribution; through user behavior analysis and network state monitoring, a self-adaptive video display control strategy is generated, dynamic adaptation of video resolution, frame rate and playing logic is realized, a full-link collaborative optimization module is constructed, terminal, network and application layer resource allocation is coordinated, a video transmission and display strategy is optimized, and network flow prediction and multi-terminal interaction requirements are combined to realize multi-terminal interaction. And generating a dynamic video layout and content switching strategy.

A computer-implemented method of using affinity profiles to determine at least one audience category that is expected to consume a selected item of content, the method comprises:obtaining affinity profiles for a plurality of users of a content distribution system, wherein each affinity profile comprises at least one selected affinity category or affinity category score, and the affinity categories are selected from a stored set of affinity categories, each representing a user's affinity for a respective subject area;determine an audience that is expected to consume the selected item of content based on the affinity profiles of the users.

The invention relates to the technical field of encryption communication, in particular to a distributed vehicle-mounted advertisement node encryption communication and tamper-proofing system. Comprising a vehicle-mounted advertisement node layer, an edge computing layer, a block chain layer and a cloud platform layer, the vehicle-mounted advertisement node layer is composed of a plurality of vehicle-mounted advertisement nodes and is responsible for collecting vehicle sensor data, playing advertisement content and performing local encryption. The edge computing layer is composed of edge computing nodes distributed in a regional base station or a road side unit and is responsible for dynamic key distribution, lightweight data verification and node state monitoring; the block chain layer comprises an advertisement evidence storage module and an identity management module, adopts an alliance chain, stores advertisement content hash, node identity certificates and operation logs, and ensures that data cannot be tampered; the cloud platform layer comprises an advertisement distribution module, a secret key life cycle module and an anomaly analysis module, and is responsible for global advertisement content distribution, secret key life cycle management and anomaly detection analysis.

The invention relates to the technical field of editing and special effect generation, in particular to a digital media content intelligent editing and special effect generation system based on artificial intelligence. Comprising a content understanding analysis module, an editing decision module, a special effect generation preview module, an audio processing module, a dynamic transition special effect module, a subtitle generation editing module, a virtual interaction module and a content distribution optimization module. The content understanding analysis module is used for video content identification and sentiment analysis; and the editing decision module is used for recommending an editing point and providing a dynamic editing strategy. The video content can be automatically analyzed, the editing point and the special effect adding position can be identified, the editing and special effect generation efficiency is greatly improved, the editing strategy and the special effect type can be dynamically adjusted according to the video content and the sentiment analysis result, the editing and the special effect can better meet the user requirement and the video content, and the user experience is improved. Abundant editing and special effect options are provided, and the editing and special effect generation process is simplified.

The invention discloses a CDN-based video downlink weak network adaptive image quality optimization method and system, and relates to the technical field of video content distribution. The method comprises the following steps: S1, generating a basic compensation amount according to frame interval deviation and frame content complexity; s2, calculating a rendering overhead index and a rendering urgency threshold according to the state of the multi-source equipment, and generating an interpolation correction coefficient for frame rendering time sequence adjustment; s3, constructing a channel damage quantization map segment trigger redundancy control and introducing an equipment load state constraint; and S4, basic waiting time is generated according to local historical features, and a final waiting time value is generated in combination with the playing buffer area state and the composite load factor. Through cooperation of frame time sequence compensation enhancement, rendering scheduling optimization and segmentation redundancy control strategies, improvement of video image quality stability and end side load adaptability in a weak network environment is realized.

The invention discloses a cross-platform content distribution intelligent adaptation method and system. The method comprises the following steps: acquiring multi-modal original input content; performing feature extraction on the multi-modal original input content to obtain a content feature group; obtaining platform feature parameters of the target distribution platform; obtaining a feature matching degree between the content feature group and the platform feature parameter; generating a content transformation scheme according to the platform feature parameters and the feature matching degree; and according to the content transformation scheme, carrying out transformation adjustment on the multi-modal original input content to obtain transformation content. According to the technical scheme provided by the invention, the original content is subjected to intelligent transformation adaptive to each platform; various content forms are supported, and the application scene is wide; quality evaluation and optimization are carried out on the transformation content, and the quality and the effect are improved; a publishing strategy is formulated, and content value maximization is achieved; fast access of a new platform is supported, a feature library is continuously optimized and updated, and a content modification scheme is dynamically adjusted; and the multi-platform operation efficiency is obviously improved.

Disclosed is a content distribution system including a content server communicatively coupled to a data packet network and running one or more server-side components. A mobile computing device also communicatively coupled to the data packet network and running a client-side component may be configured to: (a) receive from said one or more server-side components a mobile device operational scenario definition; (b) activate or configure one or more monitoring routines in accordance with the device operational scenario definition; and (c) monitor said mobile computing device for an occurrence of the defined operating scenario using the activated or configured monitoring routines.

The invention relates to the field of data analysis and cleaning, in particular to a method and system for automatically collecting and cleaning public opinion experimental data. The method comprises the following steps of performing periodic data crawling on a public information website, performing public opinion hotspot analysis, and extracting a to-be-processed hotspot event stream; performing keyword detection and global content distribution analysis on the to-be-processed hot event stream to obtain a keyword frequency distribution diagram; performing negative emotion deep recognition according to the to-be-processed hot event stream, and extracting negative emotion public opinion data; performing negative public opinion evolution trend prediction based on the keyword frequency distribution diagram to obtain a negative public opinion propagation situation; and performing IP address tracing on the negative emotion public opinion data to obtain the negative public opinion region sensitivity. According to the method, comprehensive and accurate abnormal public opinion detection and deletion are realized, and the network information quality and the public governance level are improved.

The invention relates to the technical field of Internet video content distribution and distribution, in particular to a micro and short play content distribution and distribution system. The system comprises a content management module, a user portrait module, a copyright protection module, a commercial realization module and a data analysis module, the content management module realizes efficient uploading, auditing, storage and intelligent distribution of a movie, and content retrieval and popularization efficiency is improved through accurate classification and tagging management; the user portrait module utilizes data preprocessing, feature extraction and clustering analysis to construct an accurate user model, and user experience is improved based on a personalized recommendation algorithm; the copyright protection module comprehensively guarantees content security through request verification, URL encryption, anti-theft link and a dynamic access control mechanism; the commercial realization module adopts various strategies to improve the platform profitability; and the data analysis module optimizes a content recommendation and distribution strategy through big data collection and mining, and improves the overall operation effect. According to the invention, high-quality experience is provided for the user while the rights and interests of the content creator are ensured.

The invention discloses an artificial intelligence algorithm-based e-commerce product recommendation method and system, and relates to the technical field of product recommendation. Comprising the following steps: constructing a user-behavior path flow tree by adopting a multi-criterion splitting mechanism, and generating a node path set; respectively slicing and recombining the user portrait set and the commodity portrait set, and carrying out cross combination; constructing a behavior cluster atlas to which the user belongs, projecting cross commodity nodes in the node path set and the candidate cross mapping set into an anti-cross atlas structure among behavior clusters, and extracting interaction points as a candidate recommendation set; and performing weight regression calculation on each node of the path of the user-behavior path flow tree by utilizing path probability density mapping corresponding to each cross commodity node in the candidate recommendation set, and generating a commodity recommendation sequence according to the maximum path passing probability. According to the method, the recommendation process with the behavior chain criterion and the coupling map mapping is constructed, so that the user experience is improved, and the conversion efficiency and the content distribution capability of the platform are enhanced.

The invention provides a micro-front-end multi-application architecture, a micro-front-end multi-application system and an integration method of the micro-front-end multi-application system. The method comprises the following steps: constructing a main application based on a Vite tool chain; a multi-application universal code warehouse is constructed based on Monorepo; based on the main application and the multi-application universal code warehouse, introducing a Wujie micro-front-end, and constructing a micro-front-end multi-application architecture; performing technical agreement based on a micro-front-end multi-application architecture; based on the technical agreement, transforming a main application and a sub-application which are integrated and accessed into the micro-front-end multi-application architecture, and constructing a multi-application integrated system; according to the dependency relationship of different application resources in the multi-application integrated system, public resources are planned, a CDN content distribution network is constructed, and a distribution strategy of the resources and a distribution service of the resources are constructed; performing configuration setting and construction deployment on the multi-application integrated system and the resource distribution service; according to the method, the problem of'giant application 'of enterprise-level integrated software is solved.

The invention discloses a CDN content caching method, device and equipment, a storage medium and a product. The method can be applied to the technical field of artificial intelligence, is applied to any CDN node in a content distribution network CDN, and specifically comprises the following steps: obtaining user access content data in a first preset time period; inputting the user access content data into a popularity prediction model obtained by pre-training to obtain predicted content popularity of the user access content data output by the model; and determining a target cache hierarchy of the user access content data according to the predicted content popularity, and storing the user access content data to the target cache hierarchy. According to the technical scheme, the access content hit rate of the CDN cache is improved, the CDN performance is improved, and the request processing efficiency of the user access content is improved.

To properly assist reactions from a content distributor in a field of content distribution.SOLUTION: A program causes a computer to execute the processes of: managing past content distributed by a distributor, and activity information, for each viewer, related to activities allowed for the viewers who view at least one of the past content and content currently distributed by the distributor; managing setting information related to reactions of the distributor; obtaining multiple actions from one or more viewers who are viewing the content currently distributed by the distributor; and automatically generating reaction candidates that the distributor can take for one or more specific actions out of multiple actions, on the basis of the activity information and the setting information.SELECTED DRAWING: Figure 15

The invention provides an intelligent reply system suitable for a live broadcast matrix scene. The intelligent reply system comprises a receiving module, an algorithm processing module, a reply generation module, a distribution module and a feedback closed loop module. The receiving module collects user input data and dynamic scene parameters of the live broadcast room in parallel, wherein the parameters comprise audience activeness, content sensitivity and real-time response level. The algorithm processing module dynamically integrates a real-time sentiment analysis algorithm, a semantic association algorithm and a scene adaptation algorithm through a weight distributor to generate a real-time weight. The reply generation module generates self-adaptive reply content according to the output, the distribution module configures a resource allocation strategy, and the feedback closed loop module monitors user interaction indexes in real time and adjusts weight distributor parameters. The reply content highly matched with the live broadcast scene can be generated in real time, and the user interaction experience and the live broadcast efficiency are effectively improved.

The invention discloses a three-dimensional data acquisition method and a related device, and belongs to the technical field of Internet. The method comprises the steps that a data acquisition request sent by the user terminal is received, the data acquisition request carries a target uniform resource locator URL and three-dimensional indication information, the target URL is a URL of a target virtual space, and the three-dimensional indication information indicates a target three-dimensional model in the target virtual space; acquiring data of the target three-dimensional model based on the target URL and the three-dimensional indication information; and sending the data of the target three-dimensional model to the user terminal. The three-dimensional data is sent to the user terminal through the content distribution network, the distribution speed of the three-dimensional data can be improved, the edge node closest to the user terminal serves as the first node, the first node obtains the three-dimensional data and then sends the three-dimensional data to the user terminal, and the efficiency of obtaining the three-dimensional data by the user terminal can be improved.

The invention provides a content distribution network traffic alarm method and device and electronic equipment, and aims to solve the problem of insufficient accuracy of abnormal traffic detection. The method comprises the following steps: acquiring a content delivery network (CDN) real-time traffic log, wherein the CDN real-time traffic log is generated by a CDN server; analyzing a plurality of dimension labels from the CDN real-time traffic log; for each label combination determined by the plurality of dimension labels, calculating the CDN real-time traffic log according to the label combination to obtain the peak traffic of the label combination; obtaining a CDN historical flow log, and calculating the baseline flow of the label combination according to the CDN historical flow log; and generating an alarm message of the CDN real-time traffic log according to the peak traffic of the label combination and the baseline traffic of the label combination, wherein the alarm message comprises the label combination and the peak traffic of the label combination.

The invention relates to the technical field of content distribution network resource management, and provides a resource scheduling method, device and equipment, a storage medium and a computer product, a service request is received, a feature vector of the service request is determined, and the feature vector represents the service processing complexity, the service quality level and the service weight factor of the service request; obtaining one or more of load information, performance information and fault information of the node to determine a computing power score of the node; and determining a resource scheduling strategy of the service request based on the feature vector and the computing power score. The computing power demand of the service request is measured from multiple angles, the computing power demand evaluation accuracy is improved, the resource scheduling strategy is determined based on the computing power demand of the service request represented by the feature vector and the computing power score of the node, the service computing power demand can be dynamically matched, and the resource scheduling efficiency is improved. The computing power score of the node is determined based on one or more of load information, performance information and fault information, and burst traffic and node state dynamic changes can be handled.

The invention discloses a park large-screen centralized management and control method and system of an intelligent large-screen management platform, and relates to the technical field of intelligent large-screen management, and the method comprises the steps: building the network connection between a platform and a large screen through the configuration of communication parameters and the input of large-screen equipment identification information, and completing the equipment access authentication through the network connection relation; collecting parameter information and an equipment operation state of the accessed equipment; based on the parameter information of the accessed device, setting a content distribution strategy of a display area, and executing format adaptation and split screen template configuration on the multi-format content; and receiving a voice instruction, completing user identity recognition, and executing alarm grading and display content adjustment according to the collected equipment operation state. According to the method, an access mechanism based on automatic matching of communication parameter configuration and equipment identification information is constructed, so that the access efficiency of heterogeneous large-screen equipment and the automation level of system deployment are effectively improved.

The invention discloses a back-to-source testing method, computer equipment and a storage medium, and relates to the technical field of content distribution networks, and the back-to-source testing method realizes active pushing of configuration information through a mode of sending complete configuration information to a source station server in advance before validity testing; therefore, after the source station server receives the back-to-source request of the target edge server, the configuration information carried by the back-to-source request can be finely compared with the configuration information stored in the source station server, and the back-to-source test result is fed back to the client in real time after the comparison is completed, so that the client can know the processing condition of the back-to-source request in time, and the processing efficiency of the back-to-source request is improved. And corresponding operation can be carried out in time according to the feedback result. In the whole back-to-source test process, tedious operations such as packet capturing by using a packet capturing tool at the source station server are not needed, the CDN configuration effective test can be rapidly and accurately completed, the whole test period is shortened through the rapid and efficient test process, and therefore the efficiency and quality of back-to-source test work are greatly improved.

The invention relates to the technical field of vehicle-mounted operating systems, and discloses a QNX-based vehicle-mounted operating system and an operating method.The system comprises a kernel architecture module used for providing a QNX microkernel architecture and reserving underlying functions in the microkernel architecture, and the underlying functions comprise a real-time task scheduling mechanism, a dynamic content distribution mechanism and an inter-process communication mechanism; the system service library module is used for packaging a bottom layer function and providing the bottom layer function to the upper layer function module through an API (Application Program Interface); and the upper layer function module is used for calling an API interface and realizing corresponding external service based on the bottom layer function. A QNX microkernel architecture is adopted in the vehicle-mounted operation system of the QNX, so that task scheduling can accurately and efficiently respond to various real-time requirements, and the real-time response capability of the vehicle-mounted operation system is improved.

The embodiment of the invention provides a service increment prediction method and device for a content distribution network, equipment and a medium. The method comprises the following steps: acquiring bandwidth data of a target service in a plurality of historical periods; selecting the bandwidth data of the latest historical period as reference bandwidth data according to the bandwidth data of the plurality of historical periods; determining the similarity between the reference bandwidth data and the bandwidth data of other historical periods except the reference bandwidth data; determining a preset number of bandwidth data of a target historical period according to the similarity; performing weighted average on the bandwidth data of the target historical period, and determining estimated bandwidth data of the next period; and determining target increment information of the next period according to the estimated bandwidth data of the next period. The bandwidth data of the target historical period is screened out by utilizing the bandwidth data of the plurality of historical periods, and the target increment information is determined according to the bandwidth data of the target historical period, so that the efficiency and accuracy of predicting the target increment information of the next period are improved.

The invention relates to the technical field of information transmission, in particular to a cloud computing management system and method. The method comprises the following steps: acquiring user activity data, and predicting a traffic demand according to the user activity data to obtain live broadcast predicted traffic data; obtaining cloud platform resource allocation data, and performing elastic expansion to obtain a resource allocation configuration table; performing content distribution according to the resource allocation configuration table and the live broadcast prediction flow data to obtain live broadcast content distribution data; performing live broadcast content multi-preference layer caching on the live broadcast content distribution data to obtain a cache storage optimization table; acquiring real-time live broadcast network bandwidth data, and performing video coding according to the real-time live broadcast network bandwidth data to obtain a video quality strategy table; and obtaining real-time resource allocation data of the cloud platform, and optimizing cloud resource allocation according to the real-time resource allocation data of the cloud platform to obtain optimized cloud resource allocation data. The cloud computing resource use efficiency and the communication efficiency can be improved.

The embodiment of the invention discloses a resource preheating method and a related device, and the method comprises the steps: obtaining preheating node information corresponding to a target resource, and enabling the preheating node information to be used for indicating a preheating node which carries out a preheating task on the target resource, the preheating node is determined in each access node according to operation state information of each access node corresponding to the target resource, and the access node is a content distribution network node related to a domain name to which the target resource belongs; when a resource pulling request sent by a target access node is received, determining whether the target access node is a preheating node according to the preheating node information; and when it is determined that the target access node is the preheating node, sending a resource positioning identifier of the target resource to the target access node, so that the target access node preheats the target resource based on the resource positioning identifier. According to the method, bandwidth waste and storage resource waste caused by resource preheating can be reduced, the preheating efficiency is improved, and the preheating cost is reduced.

The embodiment of the invention provides a method for displaying the content distribution of metal elements in rock based on a random forest, and can solve the technical problem that the extraction capability of geochemical elements is poor. The method comprises the following steps: confirming spectral data and metal element content of a sample, and preprocessing to obtain an effective wave band; re-sampling the effective wave band according to each sampling interval; establishing a first random forest model according to the resampling wave band and a one-leaving cross validation method, and confirming the optimal spectral width of the target element; based on the optimal spectral width, a second random forest model is established, and the element content value of the target element is obtained through inversion; performing interpolation processing on the element content values to obtain a prediction distribution diagram of the element content values; according to the element content actual measurement value of the target element, an actual measurement distribution diagram of the element content value is obtained through interpolation processing; and if the coincidence value between the predicted distribution diagram and the actually measured distribution diagram accords with a preset range, obtaining an abnormal region based on the predicted distribution diagram.

The invention discloses an emotion response analysis and distribution system and method based on campus propagation, and relates to the technical field of information processing and emotion calculation. Comprising the following steps: acquiring a comment text, user feature information, user interaction information and a content topic label; performing emotion recognition on the comment text based on the user feature information, and performing correction in combination with a preset group weight coefficient to obtain a group characterization emotion value; constructing time sequence emotion data based on the emotion value and performing trend prediction to obtain a propagation popularity prediction result; constructing a propagation topological graph by using the user interaction information, and determining an opinion leader node and a key propagation path; calculating an emotion sensitivity coefficient of the topic, and generating a distribution priority matrix; and dynamically adjusting the rhythm and range of content distribution according to the priority matrix. According to the invention, the accuracy of campus public opinion perception and the timeliness of the distribution strategy can be improved.

The embodiment of the invention provides a live video processing method and device, equipment, a storage medium and a program product, and relates to the technical field of streaming media. The method is applied to playing end equipment, and comprises the following steps: separating audio and video data in a cache, marking key video frames in the audio and video data, and analyzing supplementary enhancement information in the audio and video data; the supplementary enhancement information at least comprises synchronous clock information, and the synchronous clock information represents the time when the anchor end equipment collects the audio and video data; adjusting a cache control state according to the supplementary enhancement information; the cache control state is used for indicating to cache or discard audio and video data sent by the content distribution network server; processing the audio and video data according to the current video first frame state, and decoding and playing the processed audio and video data; the video first-frame state is used for indicating a first-frame state or a first-frame-free state. The method is used for achieving the effects of reducing the live broadcast delay and avoiding the influence of large delay on the online interaction effect.

A Content Distribution Network (CDN) may implemented as a front door to a RAG-based LLM for the purpose of semantically caching LLM responses to natural language prompts. More specifically, the CDN may also cache document citation(s) and / or user tag(s) along with the LLM response for purposes of ensuring that access permission constraints of the RAG are observed when providing cached LLM response as direct responses to semantically similar natural language prompts. Additionally, the CDN may be configured to modify and / or purge cached data from the CDN's cached memory database based on instructions received from a data access control (DAC) entity of the organization or enterprise client. This may ensure that the CDN observes any changes to the access permission constraints that might be made by the DAC entity.