45 results about "Word type" patented technology

A content processing method and apparatus, a content recommendation method, an electronic device, and a storage medium, relating to the technical field of information processing. The content processing method comprises: obtaining a plurality of pieces of historical content data which have been subjected to social interaction positive feedback in a first virtual interaction scene by a target user, wherein the historical content data comprises words or characters representing content and the semantics of the content; generating a word vector used for representing the words or the characters in the plurality of pieces of historical content data, and a word position vector used for representing the position of the words or the characters; generating a word type vector used for representing the meaning of the words or the characters, and a content position vector used for representing the position of each piece of historical content data among the plurality of pieces of historical content data; generating a user sequence representation on the basis of the vectors; and obtaining a plurality of content sequence representations, and determining a candidate content sequence representation on the basis of the similarity between the user sequence representation and each content sequence representation, content corresponding to the candidate content sequence representation being used to be recommended to the target user.

The application discloses a recommendation method and system based on reinforcement learning driving large model adaptive prompt, the method comprises the following steps: obtaining user portrait text and performing semantic similarity matching to determine the corresponding prompt word type of the user; through a deep Q network (DQN) and a confidence upper bound algorithm (UCB), a preset multiple prompt optimization strategy is selected to recommend a prompt optimization strategy and obtain the prompt optimization strategy S; based on the prompt optimization strategy S and the corresponding prompt word type of the user, a large model is used to generate an optimized prompt word, a recommendation system is used for verification and performance index evaluation; continue iteration until the preset end condition is met to obtain the optimized prompt word for application in a target recommendation system. The application aims to introduce fine-grained user portraits and reinforcement learning driving large models to optimize personalized prompts for different user groups, solve the problem of rigid soft prompt templates and insufficient personalization in existing recommendation technologies, and improve recommendation accuracy.

The invention relates to the technical field of crossing of artificial intelligence and software engineering, and discloses an AI generation code recognition method based on a multi-modal feature fusion model, which comprises the following steps of: obtaining global features of a method source code sample to be recognized, and performing word processing on the whole source code by adopting a sub-word level word processing strategy; distinguishing the sub-words based on the sub-word types to realize sub-word level separation modeling of the code stream and the annotation stream; carrying out fusion through bidirectional cross attention to obtain window-level local semantic representation; splicing the window-level text local representation and the method-level global feature to obtain a window-level fusion vector; inputting the window-level fusion vector into a classifier to obtain a window-level probability set; when the maximum probability in the window-level probability set is larger than a threshold value during prediction, the method is judged to be AI code generation, and otherwise, the method is judged to be human compiled code. According to the method, the generalization ability of the model can be improved, and the detection ability of local AI generated fragments and the engineering application feasibility are improved.

The linear grabbing and transplanting mechanism comprises a sealing plate and a profile frame which are fixedly connected, the outer surface wall of the profile frame is connected with a housing in a sliding mode, and the outer surface wall of the housing is fixedly connected with a lower plate through a connecting frame. A longitudinal moving assembly used for grabbing the transplanting mechanism to move longitudinally and a lifting assembly used for vertically moving the housing are integrated on the top of the sealing plate. According to the graphite boat cover plate, the two sets of side edge cylinder bodies are in linkage with the corresponding grippers, the two sets of side edge cylinder bodies are combined to the two opposite sides of the two sets of connecting parts at the top of the graphite boat cover plate correspondingly, then the two sets of middle cylinder bodies drive the corresponding grippers, and the two sets of grippers are combined to the two adjacent sides of the two sets of connecting parts; and the guide wheels, the guide blocks, the centering limiting plates and the boat cushion blocks on the multiple sets of grippers are all arranged in a manner of being attached to the outer contour of the connecting part, so that stable grabbing and transplanting of the graphite boat are realized.

The invention relates to a dialogue preference data construction method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring original dialogue data and a corresponding original dialogue reply; respectively constructing dialogue data generation requests for the original dialogue data, the original dialogue reply and a plurality of pre-constructed cue words corresponding to different cue word types, inputting each dialogue data generation request into a plurality of pre-constructed dialogue generation large models corresponding to different architectures, and generating candidate dialogue replies; inputting each candidate dialogue reply and the original dialogue reply as a to-be-evaluated dialogue reply into a plurality of pre-constructed dialogue evaluation large models corresponding to different architectures, and outputting dialogue preference evaluation results for each to-be-evaluated dialogue reply through each dialogue evaluation large model; and generating dialogue preference data based on the dialogue preference evaluation result. By adopting the method, the efficiency of constructing the dialogue preference data can be improved.

Systems and methods are disclosed herein for training a model to accurately determine whether two phrases are conversationally connected. A media guidance application may detect a first phrase and a second phrase, translate each phrase to a string of word types, append each string to the back of a prior string to create a combined string, determine a degree to which any of the individual strings matches any singleton template, and determine a degree to which the combined string matches any conversational template. Based on the degrees to which the individual and combination strings match the singleton and conversational templates, respectively, strengths of association are correspondingly updated.

The invention belongs to the technical field of computers, and discloses a GUI (Graphical User Interface) positioning method and system based on a routing prediction framework. According to the method, a route prediction mechanism based on lexical item type judgment is introduced in the autoregression decoding process of the multi-modal large language model, and an interface semantic generation task and a spatial positioning task are dynamically shunted, so that a user instruction with a target element can jump out of a discrete text generation path; continuous space coordinate regression is directly carried out based on a hidden state and structure enhanced interface image features, and a null positioning result is returned through a special refusal response lexical item when a target element does not exist, so that the coordinate quantization error and illusion positioning problems are effectively avoided under an end-to-end unified framework, the positioning reasoning delay is remarkably reduced, and the positioning accuracy is improved. Precision, real-time performance and robustness of graphical user interface element positioning are improved, and the overall understanding ability of the model for interface structure semantics and spatial layout relation is enhanced.

The application discloses a BLS-based NAVTEX message context intelligent decision support method, applies data cleaning, word type reduction and reference stop word operations to NAVTEX message data, and proposes a message context label to mark the categories of the message, which specifically shows that the message content contained in the navigation warning is analyzed, and six categories of message context labels are summarized.Through the application, effective information in the original message data can be accurately extracted, and strong support is provided for subsequent message context classification tasks and navigation decision support, so that the trained message features are more concise and representative.The application is based on BLS and is improved, the accuracy of the NAVTEX message context classification is improved, intelligent navigation decision support services are provided for the mariners, the working strength can be effectively reduced and the working efficiency can be improved, meanwhile, the safety navigation performance of the ship is further enhanced, and the function of the navigation aid equipment is enriched.

Embodiments of the present specification relate to a text desensitization method based on differential privacy, a program product and a computing device. The method comprises: obtaining a cluster set, any target word in any cluster has a preset replacement probability distribution, the replacement probability distribution is determined based on an exponential mechanism, and is used to describe the probability of replacing the target word with each word in the cluster; performing named entity recognition on the input text to be desensitized to determine the entity type to which each word belongs, which includes an entity type preset as a sensitive word type; for any target sensitive word belonging to the sensitive word type, it is judged whether it exists in any cluster of the cluster set, when the target sensitive word exists in a first target cluster, a target replacement word is obtained by sampling according to the replacement probability distribution of the target sensitive word in the first target cluster; and the target sensitive word in the text to be desensitized is replaced with the target replacement word to obtain a desensitized text.

The invention discloses an NLP-based method for realizing automatic transcription of hot word extraction specifications, which comprises the following steps of: presetting different scenes, defining hot word types in the scenes and constructing a common hot word library, and preprocessing and cleaning a document; automatically analyzing the cleaned context data, and automatically extracting hot words in the corresponding file content; the extracted hot words are intelligently classified, and a dynamic hot word library is constructed; meanwhile, a voice transfer result is transferred into a hot word verification module in real time; carrying out semantic analysis according to the context of the voice recognition result, judging the most coincident hot word, and carrying out replacement display on the extracted hot word result; according to the method, a normalized result of hot word replacement is displayed, a text result of speech recognition is automatically adjusted, weights of hot words in a dynamic hot word library are updated in real time, representative hot words are extracted from preprocessed texts based on a trained NLP semantic model by applying technologies such as a clustering algorithm and topic analysis, and the accuracy of transcription is improved.

The invention relates to a traffic network security event extraction method based on machine reading understanding, which performs joint training and optimization on a trigger word prediction module and an argument extraction module by sharing a coding layer of a pre-training language model, so that two tasks promote each other in a shared semantic space. Accurate context constraints are provided for argument role judgment through trigger word recognition, disambiguation of trigger word types is facilitated through argument information, and the deep interactive optimization mechanism enables the model to learn collaborative representation sensitive to the whole event structure. Therefore, the overall accuracy of event extraction and the generalization ability of the model are remarkably improved, and the inherent error propagation problem in a traditional assembly line method is solved.

1. Name of the designed product: planer blade (one word type). 2. Use of the designed product: for peeling. 3. Design points of the designed product: in shape. 4. Picture or photo best showing the design points: perspective view 1.

The application discloses a method and device for generating an information model, a controller, a medium and a product. The method comprises: obtaining description information corresponding to a device measuring point; performing word segmentation processing on the description information to obtain word segmentation results corresponding to N preset professional word types, N being an integer greater than 1; performing mapping processing on the corresponding word segmentation results according to the preset professional word types to obtain information identifiers corresponding to the word segmentation results; and generating an information model corresponding to the device measuring point based on the N information identifiers. The method can avoid the understanding of the description information corresponding to the device measuring point by different people from being biased, the information model from being greatly different, the use effect of the information model from being affected, and the generation efficiency of the information model from being improved.

The application discloses a machine reading comprehension event extraction method and device based on template bridging, and medium, the method steps comprise: step S01. Input text and trigger word question template are obtained and combined to form an input instance with a trigger word question prompt template; step S02. Syntax analysis is performed on the input instance to form an adjacency graph, the input text and the trigger word question prompt template are connected according to the adjacency graph to obtain a link graph, and global features are extracted according to the link graph; the global features and semantic features are fused to identify the trigger word and the trigger word type; step S03. A argument question prompt template is generated, the prompt template is combined with the input text to form an input instance with a question prompt template; step S04. Argument extraction is performed to obtain argument and argument type output. The application has the advantages of simple implementation method, high event extraction efficiency and precision, good portability and the like.

The invention discloses a recommendation method and system based on reinforcement learning driving large model self-adaptive prompt. The method comprises the steps of obtaining a user portrait text and performing semantic similarity matching to determine a prompt word type corresponding to a user; selecting a recommended prompt optimization strategy from a plurality of preset prompt optimization strategies through a deep Q network DQN and a confidence upper limit algorithm UCB, and obtaining a prompt optimization strategy S; based on a prompt optimization strategy S and a prompt word type corresponding to the user, utilizing a large model to generate an optimized prompt word, and utilizing a recommendation system to perform verification and performance index evaluation; and continuing iteration until a preset end condition is met to obtain an optimized prompt word to be applied to a target recommendation system. According to the method, a mechanism for carrying out personalized prompt optimization on different user groups by introducing a fine-grained user portrait and a reinforcement learning driven large model is adopted, so that the problems of stiffness and insufficient personalization of a soft prompt template in the existing recommendation technology are solved, and the recommendation accuracy is improved.

The invention provides a content processing method and device, a content recommendation method and device, electronic equipment and a storage medium, and relates to the technical field of information processing. The content processing method comprises the following steps: acquiring a plurality of pieces of historical content data subjected to social interaction positive feedback in a first virtual interaction scene by a target user, wherein the historical content data comprises words or characters representing contents and semantics of the contents; generating word vectors for representing words or characters in the historical content data and word position vectors for representing word or character positions; generating a word type vector used for representing word or character meanings and a content position vector used for representing the position of each piece of historical content data in the multiple pieces of historical content data; generating a user sequence representation according to the vector; obtaining a plurality of content sequence representations, and determining candidate content sequence representations according to the similarity between the user sequence representation and each content sequence representation; the content corresponding to the candidate content sequence characterization is recommended to the target user.

This application discloses a biomedical event assembly method, apparatus, device, and medium, relating to the field of natural language processing technology. The method includes: combining trigger words and arguments of the text to be assembled based on their trigger word types to obtain candidate events; tagging the trigger words and arguments of the candidate events using a nested tagging method to obtain candidate instances; encoding the candidate instances using a preset deep learning model to obtain an output representation of the semantic information of the candidate instances; acquiring a first probability result for a preset legal category and a second probability result for a preset illegal category of the output representation; and then determining a target biomedical event from the candidate events based on the first and second probability results. This method can improve the performance of biomedical event assembly.

The present invention proposes a controllable concurrent data desensitization method and device based on a Chinese-English sensitive dictionary. The method comprises the following steps: obtaining the data to be desensitized from the metadata library, and synchronizing the table structure of the data to be desensitized to the metadata table in the parameter library; configuring the Chinese-English sensitive dictionary table; associating the metadata table with the Chinese-English sensitive dictionary table, obtaining the table name of the metadata table with sensitive fields and storing it in file A; looping through the table names in file A, creating an isomorphic table corresponding to file A, obtaining the table structure of the isomorphic table and storing it in file B; obtaining the fields in file B and comparing them with the Chinese-English sensitive dictionary table, performing desensitization conversion according to the sensitive word type, and generating a desensitization script; inputting concurrent parameters, and executing the desensitization script concurrently to complete data desensitization. The present invention changes the value of the data while preserving its original characteristics, so that the data can still be used normally by the business while avoiding the risk of data leakage.

This invention provides an audio playback control method, apparatus, and electronic device, relating to the field of voice processing technology. The audio playback control method includes: acquiring a sampled signal and inputting it into a voice wake-up model to obtain the confidence level of the sampled signal containing a wake-up word, the voice wake-up model being used for wake-up word detection; if the confidence level is greater than a preset confidence level, extracting a signal segment containing the wake-up word from the sampled signal and inputting this segment into a type recognition model to obtain the category of the wake-up word output by the type recognition model, the type recognition model being used for wake-up word type recognition; if the category is a call intro wake-up word and the electronic device is detected to be playing audio, adjusting the current audio playback state of the electronic device. The technical solution of this invention can automatically adjust the audio playback state of an electronic device when a user connects to a callable device.

The present invention belongs to the field of Internet of Things security technology, and discloses a DGA domain name detection method for the Internet of Things botnet, including: obtaining the domain name string in the DNS domain name resolution request sent by the Internet of Things device; inputting the domain name string into the trained domain name detection model to obtain the binary classification and multi-classification results of the domain name; wherein, the domain name detection model is obtained by training based on the fusion network of the Small BERT pre-trained model and CNN. By combining the two feature extraction capabilities of the SmallBERT model at the sub-word granularity for domain names and CNN at the character granularity for domain names, the present invention improves the learning ability of the algorithm for the comprehensive features of domain name semantics, morphology, pronunciation, character randomness, etc., enhances the detection performance for random word type DGA domain names, improves the problem of performance imbalance in the domain name multi-classification task, meets the requirements of limited computing resources and high inference speed in the Internet of Things environment, and has the advantages of high detection performance, simple process, easy deployment, and wide available range.

The application discloses a construction method of a code word type EP code based on a finite field resource and a finite field multiple access method thereof, and belongs to the technical field of 6G communication. j The application discloses a construction method of a code word type EP code based on a finite field resource and a finite field multiple access method thereof, and belongs to the technical field of 6G communication. The application discloses a construction method of a code word type EP code based on a finite field resource and a finite field multiple access method thereof, and belongs to the technical field of 6G communication. The application discloses a construction method of a code word type EP code based on a finite field resource and a finite field multiple access method thereof, and belongs to the technical field of 6G communication. The application discloses a construction method of a code word type EP code based on a finite field resource and a finite field multiple access method thereof, and belongs to the technical field of 6G communication.

The embodiment of the application provides a sensitive word type determination method and device, the method comprises: obtaining a to-be-recognized text vector; inputting the to-be-recognized text vector into a three-branch attention model to obtain a sensitive word recognition result and an entity word recognition result, and obtain a weighting vector of each branch; determining a first sensitive word type corresponding to a sensitive word vector in the sensitive word recognition result from a preset sensitive word type according to the similarity between the sensitive word vector and a feature vector of the preset sensitive word type; and performing sensitive word type recognition on an entity word vector in the entity word recognition result according to the entity word vector, the feature vector of the preset sensitive word type and the weighting vector of each branch, to obtain a second sensitive word type corresponding to the entity word vector.

The embodiment of the application provides a kind of text processing method and device, equipment, storage medium, belong to artificial intelligence technical field.The method comprises: by text extraction processing to original corpus, extract the preliminary abstract text that can express the meaning of original corpus most, again according to the preset segmented text length, preliminary abstract text is divided, and target segmented text is obtained.Target segmented text is filtered to determine target candidate word group, and target candidate word group semantic analysis processing is handled, the importance of word segmentation can be determined by the word type of word segmentation, and according to the word type of word segmentation, word segmentation is linked to the preset upper and lower cognitive graph, and target upper and lower cognitive graph is obtained.Because the upper and lower information of each word segmentation and the connection between each word segmentation can be easily obtained through target upper and lower knowledge graph, therefore, the efficiency of obtaining information can be improved by the text processing method of the embodiment of the application.

Disclosed are methods, devices and systems for translating a document using neural networks and leveraging the hierarchical structure of the document. Embodiments of the disclosed technology use bi-level structures that incorporate both the unique meanings of words and unique grammatical rules on matching grammatical word types in a document to train a neural network. The trained neural network is used to translate documents in an automated and efficient manner. The disclosed embodiments advantageously use manual (or human) analysis on a small portion of text to identify the unique means and grammatical rules, which is then leveraged to translate a much larger corpus of text with increased reliability and accuracy.

The utility model provides a reinforcing device for a linear wall constructional column formwork, which comprises a first support unit and a second support unit, the first support unit and the second support unit are respectively clamped on a left wall of a constructional column, the second support unit is clamped on a right wall of the constructional column, and a plurality of supporting units are detachably connected between the first support unit and the second support unit. The supporting units are provided with crimping units used for being pressed on the side faces of the formworks, and the supporting units and the crimping units are arranged on the front sides and the rear sides of the constructional columns correspondingly. The first support unit and the second support unit are clamped on the wall bodies on the two sides of the constructional column, and in combination with rigid connection of the supporting unit, lateral pressure during concrete pouring can be effectively resisted, and formwork expansion or displacement is prevented; the crimping unit ensures that the formwork is tightly attached to the design position of the constructional column, the quality defects of slab staggering, slurry leakage and the like after pouring are avoided, and the perpendicularity and flatness of a wall are improved; the positioning assemblies and the reinforcing assemblies at the tops of the first support unit and the second support unit can be adjusted up and down, and construction of linear wall constructional columns with different heights is met.

The application discloses a forest biomass intelligent nested recognition and measurement method based on unmanned aerial vehicle remote sensing, and specifically comprises the following steps: S1, forest biomass data collection; S2, data processing; S3, information extraction; S4, nested entity boundary detection: the text paragraph information generated in S3 is processed, word segmentation and word type annotation are carried out, and the nested boundary information mentioned by each text paragraph is detected; S5, entity multi-layer information annotation: after that, the data annotated in S4 is processed, and the entity type, entity subtype and mentioned role information of each group of text paragraphs are recognized; the application proposes an intelligent nested recognition and measurement method, uses a conditional random field model to fuse a plurality of features for statistical decision, secondly, a multi-layer information annotation problem is regarded as a classification problem, two classification engine parallel modes are designed from the realization angle, and a classifier is not designed for each layer of information annotation, so that the performance is obviously improved compared with the single classifier.

Embodiments of the application disclose a two-dimensional code detection method and device, a model training method and device, equipment and a storage medium. The method comprises: obtaining a two-dimensional code region of a to-be-detected image according to a preset first detection positioning model; obtaining a square region of a back-to-word type in the two-dimensional code in the to-be-detected image according to a preset second detection positioning model; inputting the square region of the back-to-word type into a preset first classification model to obtain a first classification result of the square of the back-to-word type in the two-dimensional code; obtaining a square region of a non-back-to-word type in the two-dimensional code, and inputting the square region of the non-back-to-word type into a preset second classification model to obtain a second classification result of the square of the non-back-to-word type in the two-dimensional code, thereby avoiding the technical problem that slight defects on the two-dimensional code are not easy to distinguish, and greatly improving the precision and efficiency of two-dimensional code detection in a small circuit breaker.

The utility model belongs to curtain wall installation technical field, concretely relates to a kind of positioning auxiliary tool for curtain wall gluing, it includes: one word type positioning guide rail, one word type positioning guide rail is set horizontally, and its one side is spaced apart and is provided with several pneumatic suction accessory, and the other side is connected with the connecting seat that can be moved along one word type positioning guide rail horizontally;The connecting seat is connected with the positioning member that can be moved along connecting seat longitudinally, and the upper end of the positioning member is provided with connecting piece;Adjusting sleeve is used for fastening to be set on curtain wall glueing machine, the outside of adjusting sleeve is set with positioning sleeve, and the side of positioning sleeve is integrally provided with fixed seat;The fixed seat is rotatably connected with the connecting piece, and pivot is parallel with one word type positioning guide rail.This positioning auxiliary tool moves and positions processing when gluing by positioning guide rail, avoid the problem of poor gluing quality caused by shaking etc., and can carry out fine adjustment processing to the curtain wall glueing machine after positioning, ensure curtain wall gluing quality and efficiency.

The utility model relates to the technical field of cupping, in particular to an autonomous waist and back cupping device which comprises a grab handle, an electric control module is arranged in the grab handle, a control key electrically connected with the electric control module is arranged on the outer side wall of the grab handle, an extension rod is connected to the axial outer side end of the grab handle and is of an L-shaped structure, and the tail end of the extension rod is perpendicularly connected with an end head. An air flow channel penetrating through the end is arranged in the end, the inner side end of the air flow channel is detachably connected with a tank body, the bottom of the tank body is provided with an opening, the top of the tank body is provided with an inserting end connected with the air flow channel, the grab handle, the extension rod, the end and the tank body form a J-shaped structure, and a negative pressure pump is arranged in the air flow channel. The negative-pressure cupping device is beneficial to solving the problem that the structures of some current negative-pressure cupping devices cannot realize that a single person can not perform cupping on the waist and back areas by himself / herself.