244 results about "Copywriting" patented technology

The invention relates to the technical field of AIGC content generation, discloses an AIGC content generation method and system based on multi-modal fusion, and aims to solve the problems of decentralization, low efficiency and insufficient originality of a traditional content generation tool. Multi-modal data such as texts, images, videos and audios are integrated, user intentions are analyzed in combination with intelligent retrieval and a domain knowledge base, automatic generation from multi-modal input to high-quality creative content is achieved, a cross-modal collaborative generation technology is adopted, semantic features are dynamically aligned, and logically coherent content is generated. The content emotional value is enhanced through an emotional analysis and dynamic optimization strategy, the homogenization bottleneck is broken through, meanwhile, an automatic quality evaluation and format adaptation mechanism is integrated, deep application of scenes such as text travel, advertisement, e-commerce and interactive network television service is supported, marketing copywriting, short videos and cross-platform distribution schemes can be efficiently generated, and the market competitiveness is improved. And the content production efficiency and the creativity transmission are obviously improved.

The invention discloses an advertisement copywriting generation method and device based on multi-modal fusion, equipment and a medium, and relates to the technical field of advertisement marketing. The method comprises the steps of obtaining multi-modal data of a target video, the multi-modal data comprising visual data, auditory data and related metadata of the video, and extracting associated data from a local knowledge base; and preprocessing the multi-modal data and the local knowledge base data, and converting the multi-modal data and the local knowledge base data into feature forms which can be used for analysis. According to the method, semantic calibration is carried out on multi-modal input by means of a local knowledge base, it is ensured that generated content strictly follows domain knowledge constraints, the problem of deviation caused by the fact that a traditional model depends on implicit knowledge is solved, multi-modal information ambiguity is eliminated, collaborative semantic generation of texts, images and structured data is achieved, content dimensions are enriched, and the method has the advantages of being high in practicability and easy to popularize. And an efficient solution is provided for the landing of the intelligent generation technology in the vertical field.

The invention provides an intelligent marketing copywriting generation and effect evaluation method driven by a large language model, relates to the technical field of language models, and comprises the steps of constructing a hierarchical cross-modal knowledge graph and establishing a knowledge retrieval index. Semantic analysis is performed based on a bidirectional attention mechanism, related knowledge is retrieved by using query vectors, and an initial marketing copywriting is generated. Performing knowledge consistency verification to generate a knowledge-enhanced marketing copywriting, and generating a candidate copywriting set by adopting a diversity sampling strategy; and performing knowledge coverage, creativity and expected effect scoring on the candidate copywriting by using a multi-target evaluation network, screening an optimal copywriting through a Pareto optimization algorithm, and taking a generated path of the optimal copywriting as a positive sample to update a knowledge graph and decoder network parameters. Through knowledge graph enhancement and multi-target evaluation optimization, high-quality and high-matching-degree marketing copywriting can be generated, and the marketing effect is improved.

The invention relates to the technical field of artificial intelligence, and provides a copywriting generation method and device based on a large model, equipment and a medium. According to the method, a reinforcement learning algorithm is used for adjusting and training a copywriting generation base model formed by a large language model, so that the trained base model can generate a more reliable and high-quality copywriting; when a reinforcement learning algorithm is used for performing fine tuning training on a base model, first training is performed on the base model based on a first reward function of a rule driving class, then a second reward function is determined by using a reward model, and the first reward function and the second reward function are subjected to weighted combination to obtain a target reward function; and the base model is trained for the second time on the basis of the target reward function, so that fine-grained optimization of the base model is realized, the trained base model can generate a copywriting conforming to expectation, and the user experience is improved.

The invention discloses a marketing copywriting generation model optimization method and device and a storage medium, and the method comprises the steps: obtaining a to-be-optimized data model, and carrying out the incremental pre-training of a base model through marketing knowledge data, and obtaining the to-be-optimized data model; subjective indexes are screened through a preset evaluation index system, and screening results are integrated into objective indexes; constructing a sample data set based on the objective indexes, and training the data model by adopting the sample data set to obtain a target model; and generating a generation logic path of the target model by using a preset thinking chain decomposition model, and optimizing the target model through the generation logic path. According to the method, efficient injection and objective quantitative evaluation of marketing knowledge are realized by constructing a technical path combining a vertical field evaluation index system and incremental pre-training, and the technical effects of improving the brand integrating degree, the selling point accuracy and the commercial availability of the generated copywriting are realized in combination with an iterative optimization mechanism guided by a thinking chain.

The invention provides an interactive video generation method capable of intelligent interaction based on multi-agent cooperation and a related device, and relates to the technical field of artificial intelligence such as large language models, generative models, agents, interactive videos and the like. The method comprises the following steps: determining a user demand according to interaction between a target user and initial video content; controlling a preset copywriting agent to generate an interactive video copywriting matched with the user demand; controlling a preset interaction option generation agent and a split agent to respectively generate interaction options and split plans according to the interaction video copywriting; controlling a preset material generation agent to generate materials forming each video frame according to the mirror splitting plan; and generating an interactive video matched with a user demand from the interactive video copywriting, the interactive options and the materials according to a preset video rendering template. According to the method, through automation and agent cooperation between the main agent and each special agent, the generated interactive video can fully meet personalized and diversified user requirements, the user stickiness and the interactive experience of the interactive video are further improved, and the satisfaction degree of the user for such services or products is further improved.

The invention relates to an intelligent marketing content generation and optimization system, and belongs to the technical field of artificial intelligence and digital marketing. According to the system, through cooperative operation of the data acquisition module, the intelligent text generation module, the multi-modal synthesis module, the risk management and control module and the dynamic optimization module, whole-process closed-loop management of marketing content is realized. The data acquisition module captures unstructured data from a multi-source platform based on a user authorization protocol, semantic cleaning and structured processing are performed through a large model interface, and the problems of data dispersion and fragmentation are solved. The intelligent text generation module receives user parameters through an interactive interface, matches a preset prompt word bank, calls a large model interface to generate multi-version copywriting in batches, and supports concurrent processing of single-choice or multi-choice product lists. The multi-modal synthesis module extracts keywords according to copywriting semantics, matches pre-annotated visual materials and generates multilingual speech paraphrases, so as to ensure the consistency of graphic and text information. The risk management and control module intercepts sensitive content in real time based on an industry rule base, and guarantees output compliance. And the dynamic optimization module integrates the user behavior data to generate a delivery strategy, updates a prompt word bank and a generation model through a closed-loop feedback mechanism, and realizes dynamic adaptation of contents and market demands. Compared with a traditional method, the system has the advantages that the content generation efficiency, the cross-modal matching precision and the compliance control level are remarkably improved, and the system is suitable for the global digital marketing requirements of multiple industry scenes such as e-commerce, industrial equipment and cross-border trade.

The invention provides a content generation method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining a hotspot event according to a preset time period; performing multi-level risk factor identification on the hot events, and determining the hot events containing risk factors; for the hotspot event with each prediction result being risk factors, calculating a public attention score of the hotspot event based on an emotion vector and a topic vector of the hotspot event; when it is determined that the public attention score of the hot event is greater than a preset score threshold, determining product information of the hot event based on risk information corresponding to the hot event; and constructing corresponding copywriting content based on the title, the document content, the product information and the materials of the hot event. And generating the corresponding copywriting content. Therefore, the corresponding marketing content is accurately and quickly generated.

The invention discloses a method, a system and equipment for generating an oral video of a digital human, and a medium, and the method comprises the steps: obtaining oral copywriting and video material data, and analyzing and determining a timestamp of the copywriting in a video material through a multi-mode large model; converting the copywriting into audio data, preprocessing the audio data, and combining the audio data with the timestamp to generate first video data; and generating a digital human according to a user demand, and combining the digital human with the first video after image matting processing to obtain an oral playing video. According to the method, a traditional template generation mode is broken through, and customized production of the digital human broadcast video is realized through a multi-modal semantic matching and personalized digital human generation technology; and meanwhile, audio and video accurate synchronization, high-quality image matting and synthesis technologies are adopted, so that the content adaptability and the video quality are guaranteed, and the flexibility, the efficiency and the effect of digital population broadcast video production are remarkably improved.

The invention discloses a copywriting generation method based on artificial intelligence. The method comprises the following steps: constructing a propagation technique knowledge base and a creation technique knowledge base of an advertisement copywriting according to demand information; retrieving a matched creative strategy combination from the creative technique knowledge base, and encoding the creative strategy combination as a first cue word fragment; outputting a Top-K sub-graph, and encoding the Top-K sub-graph into a second cue word fragment; splicing the first cue word segment, the second cue word segment and the target audience portrait and style control parameters, generating a complete cue word, and generating an advertisement copywriting first draft; performing quality evaluation and generating a hallucination probability graph; and outputting the finally generated advertisement copywriting until the illusion probability output by the rewritten advertisement copywriting meets the requirement. According to the method, a closed loop of copywriting generation-evaluation-optimization is realized, and the quality of the copywriting can be effectively improved through a small number of iterations.

The embodiment of the invention provides a marketing short video generation method and device based on a large language model, and the method comprises the steps: carrying out the matching degree analysis of a hot title and product data based on the large language model, and outputting a hot topic which is most matched with a product according to the sequence of the matching degree from high to low; searching a hot video related to the most matched hot topic in a video platform, and extracting an oral copy in the hot video based on an automatic voice recognition technology; generating a creation copywriting by using a large language model based on the oral copywriting, the hot topics and the product data; and performing similarity matching on the embedded vector corresponding to the created copywriting and the semantic vector of the video slice in the database, and sorting and generating a mixed video meeting the duration requirement according to the similarity.

The invention discloses a commodity copywriting generation method based on a conditional variation automatic encoder and retrieval enhancement, which comprises the following steps: designing a reasoning module, a generation module, an evaluation module, a memory module and a prompt engineering module, aiming at user input content, based on a graph neural network, adopting path pruning and multi-hop reasoning, and generating a commodity copywriting in the reasoning module; pruning of a low-score path is achieved through path reasoning, the reasoning efficiency is improved, and an implicit relation is reasoned; the generation module introduces a layer-by-layer variational auto-encoder and enables the generated candidate commodity copywriting to meet specific condition requirements through conditional variables, the evaluation module performs comprehensive scoring on the candidate commodity copywriting, the memory module is constructed to store conversation between a user and the generation module, and the prompt engineering module performs iteration of a preset round based on a thinking tree structure. According to the method designed by the invention, the personalization and reality sense of the copywriting can be improved, and the generation of diversified advertisement copywriting with clear styles is realized.

The invention provides a video processing method and device, equipment and a medium. A specific embodiment of the method comprises the following steps: acquiring an original video; based on the original video, obtaining a video copywriting in a text form; based on the original video and the video copywriting, utilizing a target large model to generate a target text for adding a packaging effect to the original video; the target text comprises a plurality of packaging elements in a text form; and rendering the original video based on the target text to obtain a target video with a packaging effect. According to the embodiment, the existing video is packaged and edited, so that the packaged and edited video has a better effect, the packaging and editing efficiency is improved, and the user experience is improved.

The embodiment of the invention provides an information processing method and device, and the method comprises the steps: collecting hotspot information related to a target service, and obtaining a hotspot video related to the hotspot information and a reference video copywriting of the hotspot video through a target interface; inputting the hotspot information, the hotspot video and the reference video copywriting into a large language model for processing to obtain a target video copywriting matched with a target platform content publishing style; generating a target audio and a target image corresponding to the target video copywriting, and constructing a target video according to the target audio and the target image; and publishing the target video on the target platform according to a preset publishing strategy.

The invention discloses a multi-language advertisement creative generation system, and the system comprises a data collection and preprocessing module which is responsible for collecting text travel and language data, and carrying out the cleaning and marking. The culture feature analysis and modeling module extracts culture features in the data and constructs a culture model to map features and language expressions. The creativity generation module constructs a semantic understanding model based on deep learning, is in butt joint with the culture model, and generates creativity themes and plots. And the language generation module inputs the creative theme and the target language into a language generation model and outputs an advertisement copywriting. And the multi-language optimization and integration module optimizes the copywriting of each language and integrates the copywriting into an advertisement creative set. And the user interaction and feedback module provides an interface, inputs text travel items, target languages and parameters, outputs copywriting, and optimizes the system according to user feedback. According to the invention, the generation efficiency of the advertisement creativity can be improved, the adaptability of the advertisement copywriting in different language culture environments is enhanced, and the limitation of traditional advertisement creativity generation can be broken through.

The invention relates to the technical field of copywriting analysis. The intelligent copywriting analysis method comprises the steps that based on user input information, an analysis task is generated, a task identifier is distributed to the analysis task, the analysis task is stored in an analysis storage database, meanwhile, the state of the analysis task is set to be an initial state, and the analysis task is stored in the analysis storage database; the initial state comprises to-be-executed or in-execution; when the state of the analysis task is to be executed, determining the execution opportunity of the analysis task based on a preset task scheduling strategy, and updating the state of the analysis task to be in execution; when the state of the analysis task is in execution, reading corresponding user input information from an analysis storage database according to the task identifier; semantic features and syntactic structures of information input by a user are extracted, key information in a text is recognized, and a corresponding analysis task type is matched according to the key information; and obtaining an analysis calculation result. The method has the effect of improving the copywriting analysis efficiency.

The invention provides a video dubbing language conversion method, a video dubbing language conversion system and related equipment. The method comprises the following steps: acquiring audio track data from a video to be converted; carrying out human voice extraction on the audio track data and classifying according to roles to obtain a single speaker audio of each role; performing voice-to-text conversion on the single speaker audio of each role to obtain an original language copywriting of each role; performing sound cloning on the single speaker audio of each role to obtain a timbre model of each role; performing target language translation on the original language copywriting of each role to obtain a translated copywriting of each role; based on the translation copywriting of each role and the tone model of each role, performing text-to-voice conversion to obtain a translation audio of each role; and performing replacement of each role translation audio on the audio track data in the to-be-converted video to obtain a dubbing conversion video. According to the technical scheme, language video dubbing conversion combined with the tone of the speaker is achieved, the video is more diversified, and the user requirements can be better met.

The invention provides an automatic video generation method and device, equipment and a medium, and relates to the technical field of video production. The method comprises the following steps: acquiring video related information input by a user, and generating copywriting content according to the video related information and a preset copywriting script material library; according to a preset sound material library, converting the copywriting content into audio by using a text-to-voice conversion technology to obtain an audio material; according to the audio material, a digital human-driven technology is utilized, and a preset image material library and a video sub-mirror material library are combined, so that a visual material synchronized with the copywriting content is obtained; according to a preset packaging element material library, obtaining a packaging material matched with the copywriting content; and performing video synthesis and packaging on the audio material, the visual material and the packaging material to obtain a final video. According to the method, related materials can be generated through accurate matching and intelligent recommendation according to user requirements and recent popularity, a mixed cutting type and generation type material fusion arrangement mechanism is combined, one-key film formation is achieved, and the video production efficiency is improved.

The invention discloses a marketing copywriting generation method and device and a storage medium, and relates to the technical field of natural language generation, and the method comprises the steps: obtaining a to-be-optimized original marketing copywriting, a structured tag and environment variable information; inputting the original marketing copywriting, the structured tag and the environment variable information into a causal reasoning generation model; in response to a virtual intervention instruction of a user on at least one target intervention label in the structured labels, executing anti-factual reasoning through a causal reasoning generation model, generating an optimized marketing copywriting corresponding to the virtual intervention instruction, and calculating a corresponding predicted interaction amount; and outputting the optimized marketing copywriting and the predicted interaction amount. According to the method, the anti-factual causal reasoning and the large language model generation capability are fused, the user is supported to preview and optimize the copywriting and the interaction effect in real time through the virtual intervention label, multi-strategy low-cost and efficient simulation evaluation is realized on the premise that real delivery is not needed, and the intelligent level, the decision-making efficiency and the result interpretability of copywriting optimization are remarkably improved.

The invention provides an automatic marketing document generation method and device based on reinforcement learning and a storage medium. The method comprises the following steps: performing semantic matching retrieval on public copywriting data to obtain candidate copywriting; inputting the slot rewriting instruction into a pre-generated language model to generate a first marketing copywriting; performing supervision fine tuning training on a preset basic language model to obtain a first training model; inputting new user product information and promotion requirements to the first training model, generating a second marketing copywriting, scoring the second marketing copywriting and generating evaluation data; constructing a partial sequence training sample according to the evaluation data, taking the partial sequence training sample as a reward signal, and executing reinforcement learning training on the first training model to obtain a second training model; and calling the second training model in the copywriting generation system, and outputting the target marketing copywriting based on the product information and the promotion requirement of the user. According to the method and the device, high-compliance and multi-constraint consistent marketing copywriting batch generation can be realized.

The invention discloses a multi-modal data fusion and dynamic modeling tourism preference recommendation method, which comprises the following steps of: collecting fusion media data related to tourism spots from tourism websites, social media and tourism forums, processing and analyzing the fusion media data to obtain a comprehensive feature vector, and constructing a knowledge base; the method comprises the following steps: collecting travel behavior data of a user in different time periods, extracting key features, analyzing and processing based on a prediction model to obtain a user travel preference feature vector, comparing in a knowledge base according to the user travel preference feature vector, and retrieving a plurality of contents conforming to the user travel preference. And generating a plurality of recommended copywriting by adopting a generation model according to the retrieval content, and pushing the recommended copywriting. According to the method, the accuracy of tourism recommendation and the user satisfaction are effectively improved by fusing multi-modal data, capturing the tourism preference of the user in real time by utilizing a dynamic modeling technology, generating personalized recommendation content in combination with an RAG stream, introducing advanced technologies such as an attention mechanism and a graph neural network, and performing incremental learning by relying on a knowledge base.

The embodiment of the invention provides a copywriting generation method and a multi-modal information generation method. The copywriting generation method comprises the following steps: determining a target object and a user group associated with the target object; constructing a multi-dimensional copywriting set for the target object, selecting a matched copywriting matched with the user group in the multi-dimensional copywriting set, and determining a reference copywriting in the multi-dimensional copywriting set; constructing a copywriting generation sample pair according to the matched copywriting, and constructing a copywriting preference sample pair according to the matched copywriting and the reference copywriting; and optimizing a large language model based on the copywriting generation sample pair and the copywriting preference sample pair, and generating a target copywriting corresponding to the target object by using the optimized large language model.

The invention discloses an automatic advertisement creativity generation method and system based on natural language generation. According to the invention, through establishing a keyword and context construction module, a brand semantic modeling and control module, an industry trend extraction module, an advertisement generation engine, a diversity control module and a putting adaptation and post-processing module, automatic generation of advertisement originality is realized. The system firstly receives a keyword and a mood instruction input by an advertiser, and constructs an initial semantic context; and then, coding a brand sample text by utilizing a pre-training model, and generating a brand semantic center vector as a prompt embedding so as to guide the generated content to accord with brand tonality. Meanwhile, through a keyword reservation supervision mechanism, it is ensured that core keywords appear naturally and at high frequency in the process of generating the copywriting. In the generation process, the system also uses a sampling strategy through a diversity control module and uses a semantic vector to remove duplication, and finally outputs diversified and non-redundant high-quality advertisement copywriting.

The embodiment of the invention discloses a data annotation method and device, electronic equipment and a storage medium. The method comprises the steps that a to-be-labeled data set and a first cue word are acquired, the to-be-labeled data set comprises multiple pieces of advertisement copywriting data obtained after normalization processing, and the first cue word is used for preliminarily labeling the multiple pieces of advertisement copywriting data; a to-be-labeled data set and the first cue word are input into a labeling model, a preliminary labeling result corresponding to the to-be-labeled data set output by the labeling model is obtained, and the labeling model is a large language model; based on the preliminary labeling result, a target prompt word is constructed, and the target prompt word is used for indicating labeling of the multiple pieces of advertisement copywriting data according to the label meaning of the labeling label; and inputting the target prompt word and the to-be-labeled data set into a labeling model, and obtaining a target labeling result corresponding to the to-be-labeled data set output by the labeling model.

Along with continuous development of technologies such as deep learning and natural language processing, the AI model shows powerful capabilities in the aspects of understanding user intentions, processing complex information, realizing accurate matching and the like. The large star model is a large AI model which is developed by China Telecom and is based on an advanced Transform architecture. The Transformer architecture obtains significant results in the fields of natural language processing, image recognition and the like due to good expandability and strong performance of the Transformer architecture. When the method is applied to a customer service scene, the large star model can deeply understand the appeal of the user. Through natural language processing and semantic understanding technologies, the model can accurately identify and analyze questions of a user and quickly give corresponding answers or suggestions. In addition, the large star model also has strong copywriting generation ability and knowledge question-answering ability, can provide personalized exchange recommendation and shopping preferential information for the user, and further improves the user experience.

The invention discloses an automatic video editing method and system for film list recommendation, and the method comprises the steps: obtaining film data, and carrying out the preprocessing of the film data; according to the preprocessed film data, generating a recommendation list and basic data of a film list by utilizing a preset large model and cue words; generating a copywriting corresponding to the film list data according to the recommendation list and the basic data, and selecting corresponding film resources and background music; and according to the copywriting, the film resource and the background music, performing video synthesis editing, and outputting an automatic edited video recommended by a film list. According to the method, the material combinatorial logic can be dynamically adjusted according to the sheet theme, deep mining and structured application are performed on the sheet recommendation data, and high-efficiency and large-scale sheet recommendation video generation is realized.

The present invention provides a copywriting generation method, device, electronic device, and storage medium, wherein the method includes: obtaining multiple images and / or an initial requirement description for a copywriting to be generated input by a user; based on a copywriting generation model, applying the multiple images and / or the initial requirement description to generate the copywriting to obtain a first draft of the copywriting; obtaining a modification requirement description for the first draft of the copywriting input by the user; based on the copywriting generation model, applying the modification requirement description, or applying the multiple images and the modification requirement description, to modify the first draft of the copywriting to generate a target copywriting. By supporting multimodal input and introducing interactive and iterative mechanisms, the present invention can not only meet the interactive needs of users for free editing, but also improve the efficiency and accuracy of copywriting generation, providing users with a more efficient, accurate, and flexible copywriting generation experience.

The present invention discloses an intelligent copywriting method and system based on AIGC, which relates to the technical field of computing models, including a data acquisition unit, a model building unit, a copywriting generation unit, a copywriting evaluation unit and a copywriting optimization unit. The present invention obtains an AIGC model through recurrent neural network training, automatically generates a primary push copywriting according to a push purpose, a push display mode and preferred keywords, extracts comparison keywords based on the primary push copywriting, retrieves the copywriting content with the highest reading rate from the user's historical click records and historical reading records as the comparison copywriting, performs feature extraction on the comparison copywriting and the primary push copywriting to perform copywriting evaluation, corrects the AIGC model according to the copywriting evaluation result to obtain an optimized AIGC model, inputs the push purpose, the push display mode and the preferred keywords into the optimized AIGC model again to obtain an optimized push copywriting, provides a personalized copywriting generation process, and improves the accuracy of copywriting generation.

The invention relates to an advertisement information personalized recommendation method and system based on generative AI, and the method comprises the following steps: S1, obtaining user behavior data and advertisement content data, and carrying out the preprocessing; s2, pre-training is carried out based on the generative AI, and the generative AI is finely adjusted according to the preprocessed user portrait and the advertisement material library to obtain an advertisement copywriting generation model; s3: according to the preprocessed user portrait and the advertisement material library, scoring and sorting the advertisement through a recommendation model to obtain an optimal advertisement; s4, based on the optimal advertisement, generating a model by using the advertisement copywriting, and generating a recommended advertisement copywriting according to the context of the user; s5, according to the keyword of the recommended advertisement copywriting, generating a picture conforming to a brand style through an image generation model; and S6, collecting interaction data between the user and the recommended content, and optimizing the image generation model and the advertisement copywriting generation model through reinforcement learning.

The invention relates to the field of artificial intelligence, and discloses a copywriting semantic recognition system and method based on big data, and the system comprises a data collection module which collects copywriting data from a plurality of data sources, automatically collects new data at a set time interval, and carries out the preprocessing of the collected data, repeating data and format error data are removed; the data source comprises a webpage, a social media platform and a document database; the big data storage module stores the preliminarily cleaned copywriting data; the semantic recognition model training module is used for training a semantic recognition model by using the data stored in the big data storage module; the semantic recognition execution module is connected with the semantic recognition model training module and the big data storage module, a trained semantic recognition model is used for conducting semantic recognition on newly-input copywriting, a recognition result is output, and the recognition result at least comprises subject classification, emotional tendency judgment and key semantic information extraction of the copywriting.