53 results about "Digital text" patented technology

A computer-implemented method includes generating to a display device a graphical user interface (GUI), the display device being coupled to at least one processing device. A file-icon reception field is generated within the GUI. A command to move into the reception field an icon representing a digital text file containing a data set is received from a user. The digital file is accessed. A table of contents characterizing the data set is generated, one or more portions of the data set based on the table of contents are displayed in the GUI.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a digital data visualization from data of an analytics database. In particular, in some embodiments, the disclosed systems receive a digital text prompt that includes a target digital data visualization description. Furthermore, in some embodiments the disclosed systems generate visualization token predictions from the digital text prompt utilizing a language machine learning model. Moreover, in some embodiments the disclosed systems modify the visualization token predictions to generate refined visualization tokens and generates the digital data visualization based on the refined visualization tokens.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that modifies parameters of a fused feature extractor. In particular, the disclosed systems generate inferred masks from digital images and digital text prompts using a fused feature extractor. Furthermore, the disclosed systems identify a subset of the inferred masks that satisfy a validity threshold. Moreover, the disclosed systems generate an augmented training set by combining the subset of the inferred masks with a training set that includes the ground truth masks. Further, the disclosed systems generate object mask predictions from the augmented training set and determine ground truth and pseudo measures of loss by comparing the object mask predictions with the inferred masks and the ground truth masks. From the ground truth and pseudo measures of loss, the disclosed systems modify parameters of the fused feature extractors.

The invention discloses a house type recognition and three-dimensional reconstruction method and system based on grating images, and belongs to the technical field of house type image recognition. The method comprises the steps of 1, collecting and screening high-quality house type images suitable for national conditions of China regions, and constructing a grating house type image vector data set; 2, identifying walls, doors, windows and scales in the house type image based on a key point detection network, and generating and screening candidate primitives through an axial alignment rule and a constraint condition; step 3, detecting and positioning the endpoints of the scale by using a mode of combining Yolov8 and Shii-Tomasi angular point detection, and performing scale digital character recognition through a pre-trained multi-mode optical character recognition model OFA-OCR (Orthogonal Frequency Amplification-Optical Character Recognition); and step 4, designing and realizing a house type identification and three-dimensional reconstruction system based on a WebGL framework, and supporting rendering of reconstructed wall and door and window views, interaction of a user to the reconstructed house type, and forward and backward functions of house type operation historical records.

The invention discloses a micro course generation method based on OCR recognition and a server, and relates to the field of image data processing, and the method comprises the steps: collecting maintenance record document image data, and carrying out the optical character recognition processing of the maintenance record document image data, and obtaining digital text data; performing natural language processing on the digital text data according to a preset bidirectional encoder representation model, and integrating the terminology information, the fault code information and the operation step information into structured knowledge data; obtaining a knowledge level parameter and a post information parameter of the target user, and performing difficulty grading on the structured knowledge data according to the knowledge level parameter to obtain difficulty grading knowledge data; performing knowledge range screening in the difficulty grading knowledge data according to the post information parameters to obtain target knowledge data; and selecting teaching materials matched with the target knowledge data from the knowledge resource library, and generating a micro course resource bundle according to the teaching materials. By implementing the method, the updating efficiency of the training data can be improved.

The invention belongs to the technical field of natural language processing, and discloses a large language model interface calling method based on privacy protection, which specifically comprises the following steps of: 1, privacy entity content identification: identifying privacy entity content in a text through regular expression matching, named entity identification and self-defined dictionary matching technologies, the information is sensitive information in the text. According to the method, sensitive data is changed through a method of calling a large language model interface by utilizing a privacy protection technology and modes of replacing random values, changing letters into random letters, changing numbers into random numbers and randomly replacing characters with characters, so that the format of original data can be reserved to a certain extent; meanwhile, safe transmission and accuracy of the data (especially when sensitive information is involved) on the internet can be guaranteed, the privacy leakage problem existing in the large language model calling process can be effectively solved, and the safety privacy of the data is protected.

The invention, which relates to the technical field of digital interaction, discloses a block-chain-based scenic spot digital creative and creative interaction method comprising the following steps: obtaining tourist block chain identity information and initializing a creative and creative interaction context; carrying out multi-point geographic space binding according to the interaction context to obtain a content triggering set; performing identity binding mapping according to the content triggering set to obtain a to-be-casted collection set; on-chain registration is carried out according to the to-be-cast collection set, and a right-confirmed collection set is obtained; performing multi-dimensional grouping and layering according to the right-confirmed collection set to obtain an associated collection relation graph; and carrying out interactive on-chain combination according to the associated collection relationship graph to obtain the composite cultural assets. According to the method, the distribution accuracy is improved, the exclusiveness and emotion recognition of the generated digital cultural and creative collections are increased, the irreplaceability and identity exclusiveness of the collections are improved, map nesting and layering of multi-dimensional grouping are realized, the structural hierarchy is increased, and the individuation degree of cultural assets of different tourists is improved.

The invention belongs to the technical field of digital text information processing, and particularly relates to a commodity feature automatic extraction method and system based on large model semantic understanding. Existing commodity information is utilized to construct a training set and a verification set, deep understanding and semantic extraction of the commodity information are realized, during feature proofreading, feature vectors are divided into key vectors and non-key vectors, key parts and non-key parts of commodity features are analyzed emphatically, weights are distributed according to the importance of the key parts and the non-key parts, an extraction result is further optimized, and the accuracy of feature proofreading is improved. The change trend of the feature vectors in the calibration process is dynamically captured, so that an efficient small sample set is constructed, an optimal feature extraction model is screened out, a multi-step extraction mode or a single-step extraction mode can be selected according to the difference of the features during subsequent extraction of new commodity features, the accuracy and efficiency of feature extraction are improved, and the accuracy and efficiency of commodity feature extraction are improved. In practical application, commodity features meeting requirements can be extracted more quickly and more accurately.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a machine learning model to determine predicted client intent classifications and generate personalized digital text reply options within an automated interactive digital text thread. For example, disclosed systems utilize the machine learning model to generate predicted client intent classifications and corresponding intent classification probabilities. The disclosed systems utilize the predicted client disposition classifications and the disposition classification probabilities to generate personalized digital text reply options. Moreover, the disclosed systems can provide personalized digital text reply options to a client device within an automated interactive digital text thread, bypassing the inefficiency of menu options or protocols utilized to guide clients to terminal information.

The present disclosure offers an improved user interface for selecting and entering special characters in digital text, among other capabilities. When a character key is press and held, a related special character is displayed at a text cursor or input insertion point, replacing the previously displayed keyboard character. When the key remains held down, other related special characters are automatically cycled in a continuous loop until the key is released. Display of special characters are prioritized based on various criteria, including usage history and contextual factors. This enhances typing efficiency by reducing the number of keystrokes and / or mouse movements conventionally required, thus simplifying the input of special characters. It is particularly useful for multilingual users and those requiring access to special characters. The system is adaptive, learning from user behavior to improve accuracy and relevance over time.

The invention discloses a floating character presentation method of real-time information on a touch screen terminal and a user interface. According to the method, a floating window with the transparency lower than 10% is created, and real-time information symbols are displayed on the floating window, so that information is presented in a floating symbol form. The method specifically comprises the following steps: acquiring real-time data from a server; creating a transparent floating window; the data are converted into numbers, characters or graphic symbols and displayed in a high-contrast mode; and a user is supported to perform touch interaction and drag-and-drop operation through the floating window area. The user interface is characterized in that the background of the floating window is almost transparent, information symbols are clearly visible and can be dynamically updated, and the position of the floating window can be freely adjusted. The problem that real-time information display interferes with user operation in the prior art is solved, and the method is suitable for scenes needing non-intrusive information display such as financial quotation and weather early warning.

A computer server configured to perform digital image processing is disclosed herein. In one embodiment, upon receiving a transcription command, the computer server performs text recognition based on patterns in a digital image to generate digital text data corresponding to the digital image. The computer server can then determine a content format of the digital text data based on the imported digital image, and automatically apply the determined content format to the generated digital text data. The digital data can then be inserted into an electronic message and sent to a destination along with the inserted typeset digital text data.

The invention relates to a digital picture book generation method and system. The digital picture book generation method comprises the steps of input receiving, input standardization, capability judgment, multi-modal analysis, page-by-page planning, page-level verification, execution generation and auditing disk falling. Compared with the prior art, the method has the advantages that whether the AI image generation model supports the reference image or not is judged in the reference image input stage, whether the AI image generation model meets the multi-modal execution condition or not is judged in the picture book generation stage, double-layer capacity judgment guarantee is achieved, and a reliable degradation strategy is set; when the AI image generation model does not support the reference image or the analysis of the reference image fails or the AI image generation model does not meet the multi-modal execution condition, degrading to generate a digital text picture book so as to keep stable output; and through a reproducible, verifiable page list generated page by page, the context is referenced across stages.

The invention relates to the technical field of text travel service recommendation, in particular to a digital text travel-oriented service recommendation method. The method comprises the following steps: establishing a sequence set according to text travel destinations browsed by a user on a text travel APP, and calculating interestingness of the user on each text travel destination in the sequence set based on a browsing behavior track of the user on the sequence set; the method comprises the steps of collecting interaction behavior data of a user for each text travel destination on a text travel APP, constructing a user-text travel destination interaction diagram based on the interaction behavior data, calculating the tendency degree of the user and each text travel destination based on the user-text travel destination interaction diagram, determining a text travel destination recommendation sequence based on the interestingness and the tendency degree of the text travel destination, and recommending the text travel destination to the user. And the touring route of each travel destination in the destination recommendation sequence is sequentially generated according to the recommendation sequence of the destination recommendation sequence, and the touring routes are pushed to the user, so that the dynamic interest of the user can be accurately captured, and the accuracy of travel destination recommendation is improved.

Methods, systems, and non-transitory computer readable storage media are disclosed for correcting entity detection errors with entity correction and resolution in optical character recognition for digitization of physical documents. Specifically, the disclosed system utilizes named entity recognition to extract entities from character strings (e.g., words) in a digital text document. The disclosed system also tokenizes the character strings in the digital text document based on attributes of the character strings. Furthermore, the disclosed system compares the extracted entities and tokenized character strings to determine similarity metrics between the extracted entities and tokenized character strings. The disclosed system also compares extracted entities to character strings including special / numerical characters to determine similarity metrics indicating correlation probabilities between entities and character strings. The disclosed systems generate mappings between the tokens and entities based on the similarity metrics to resolve entities to likely corresponding character strings while correcting for errors during entity extraction.

Methods, systems, and non-transitory computer readable storage media are disclosed for correcting entity detection errors with entity correction and resolution in optical character recognition for digitization of physical documents. Specifically, the disclosed system utilizes named entity recognition to extract entities from character strings (e.g., words) in a digital text document. The disclosed system also tokenizes the character strings in the digital text document based on attributes of the character strings. Furthermore, the disclosed system compares the extracted entities and tokenized character strings to determine similarity metrics between the extracted entities and tokenized character strings. The disclosed system also compares extracted entities to character strings including special / numerical characters to determine similarity metrics indicating correlation probabilities between entities and character strings. The disclosed systems generate mappings between the tokens and entities based on the similarity metrics to resolve entities to likely corresponding character strings while correcting for errors during entity extraction.

The invention belongs to the technical field of digital text editing, and particularly relates to an OFD document modification system and method oriented to cloud collaboration, computer equipment and a computer readable storage medium. The client comprises an operation layer, and the server comprises a coordination layer and a conflict decision layer; the operation layer is dominated by an OT algorithm, and real-time compression of operation is carried out by adopting an incremental patch mechanism of the OT algorithm; the method comprises the following steps: predicting subsequent operation of a user through an LSTM neural network, locally pre-generating an operation chain, and when prediction accuracy is greater than a preset threshold, sending the pre-generated operation chain to a server; adding a unique mark to each operation sent to the server; the coordination layer is dominated by a CRDT algorithm, performs type judgment on received operation, processes the operation in different modes, combines all results and performs dual-structure storage on combined versions, and the conflict decision-making layer performs conflict detection after the versions are combined. According to the invention, conflicts caused by simultaneous editing by multiple persons can be reduced, and editing efficiency is improved.

Methods and systems for processing audio information to identify persons of interest in regard to a public-safety incident. An example method includes receiving human-generated narrative statements as audio and converting the narrative statements into corresponding digital texts. The method further includes determining incriminating scores for each of the narrative statements by identifying, in the digital texts, incident information classified as not being publicly known. The method further includes determining a cumulative score for an individual based on the incriminating scores tagged to the individual, making a determination of whether the individual is a person of interest based on a comparison of the cumulative score with a fixed threshold, and performing at least one automated responsive action based on the determination.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that generates a digital data visualization from data of an analytics database. In particular, in some embodiments, the disclosed systems receive a digital text prompt that includes a target digital data visualization description. Furthermore, in some embodiments the disclosed systems generate visualization token predictions from the digital text prompt utilizing a language machine learning model. Moreover, in some embodiments the disclosed systems modify the visualization token predictions to generate refined visualization tokens and generates the digital data visualization based on the refined visualization tokens.

1.The name of the design product: stator wire body layout module of linear motor graphic user interface for electronic device. 2.The use of the design product: an electronic device. 3.The design points of the design product: in the solid line drawing part of the graphic user interface. 4.The picture or photo that best shows the design points: front view. 5.The use of the graphic user interface: the overall appearance design of the interface is used to design the linear motor, and the partial appearance design of the interface is used to interact and show the layout design of the stator wire body of the linear motor. 6.The human-computer interaction mode of the graphic user interface: for the front view, the drawn stator wire body can be displayed in the display bar, and after setting the wire body parameters of the stator wire body through clicking or inputting and the like in the operation bar, the data calculated based on the wire body parameters can be displayed in the display bar. 7.Other circumstances that need to be explained: the “×” in the interface can represent numbers, characters, patterns, or a combination of at least two of them. The claimed design does not include the part of the interface content represented by the dashed line.

A system processes clinical guidance to enhance patient care management. The system receives clinical guidance in digital text form from authoritative medical sources. A large language model analyzes the received clinical guidance to extract key information and relationships. The system generates a structured pathway based on the analyzed clinical guidance. The generated pathway represents a comprehensive summary for a specific disease state, organized into logical steps. These steps encompass treatment goals, management strategies, and measures for preventing complications. The system integrates the generated pathway information into an electronic health record (EHR) system. Within the EHR, the system produces a patient chart incorporating the derived pathway information.

This invention provides a method and apparatus for generating digital SMS content, relating to the field of data processing technology. The method involves obtaining first historical marketing SMS information from a first merchant; obtaining first SMS content elements and second SMS content elements based on the first historical marketing SMS information; obtaining a first degree of influence of the first SMS content elements on the marketing effect of the first merchant and a second degree of influence of the second SMS content elements on the marketing effect of the first merchant; determining whether both the first degree of influence and the second degree of influence exceed a first preset threshold; when the first degree of influence and / or the second degree of influence exceed the first preset threshold, obtaining a first SMS content template based on the first SMS content elements and / or the second SMS content elements; and obtaining a first optimal SMS content based on the first merchant's first marketing task and the first SMS content template. This achieves the technical effects of improving readability and conversion rates, realizing precise marketing strategies, and increasing output value.

1. The name of the design product: the graphical user interface of the early warning scoring system of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. The design product only involves the graphical user interface, and the rear view, left view, right view, top view and bottom view are omitted. 6. The use of the graphical user interface: as an early warning scoring system in the medical field. 7. The human-computer interaction mode of the graphical user interface: the front view is the main interface, which displays the early warning scoring, user basic information, and displays the scoring time and the next scoring time; in the front view, clicking on any user's row jumps to the change state diagram 1, which displays the detailed information of the user; in the change state diagram 1, clicking the envelope-shaped button in the interface jumps to the change state diagram 2, and a window for sending a message reminder to other devices is popped up, in which the information can be edited by oneself, and clicking the send button. 8. Other circumstances that need to be explained: "XX" in the interface represents letters, numbers, characters and / or combinations thereof, and its content can be changed.

A method for calculating the correlation of the complete textual contents of one document to another one or many documents, to assess, compare and improve the responsiveness of one document to another, of which many possible uses are contemplated. This method comprises deconstruction of each word within said documents into its root form and the application of statistical metrics, then generating various visual presentations of that correlation and associated data. Further, the method is implemented in a system of software code and algorithms. The method and system have great utility for the User in determining the degree of responsiveness of one document to the other; one embodiment being to improve the responsiveness of a business proposal to a business solicitation. Many other embodiments may be contemplated across many disciplines which use digital text documents for analysis, comparison, evaluation, and decision making.

1. The name of the design product: graphical user interface for switching learning modes of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: the graphical user interface. 4. The picture or photo that best indicates the design points: interface change state diagram 1. 5. The use of the graphical user interface: for switching different learning modes to learn and train knowledge points. 6. The human-computer interaction mode of the graphical user interface: after the main view is loaded, enter the synchronous hierarchical learning mode of interface change state diagram 1, click "special breakthrough practice" to enter interface change state diagram 2, click "mother topic cultivation practice" to enter interface change state diagram 3, click "famous roll preparation practice" to enter interface change state diagram 4, click "mistake accurate practice" to enter interface change state diagram 5, and click "my" to enter interface change state diagram 6. 7. Other circumstances that need to be explained: "X" in the graphical user interface is replaceable numbers, words, letters or symbols; the gray area in the graphical user interface is replaceable content screen.

A method for calculating the correlation of the complete textual contents of one document to another one or many documents, to assess, compare and improve the responsiveness of one document to another, of which many possible uses are contemplated. This method comprises deconstruction of each word within said documents into its root form and the application of statistical metrics, then generating various visual presentations of that correlation and associated data. Further, the method is implemented in a system of software code and algorithms. The method and system have great utility for the User in determining the degree of responsiveness of one document to the other; one embodiment being to improve the responsiveness of a business proposal to a business solicitation. Many other embodiments may be contemplated across many disciplines which use digital text documents for analysis, comparison, evaluation, and decision making.

A system, method, and computer program product for implementing automated digital text optimization is provided. The method includes receiving during execution of an Internet search process, digital textual content comprising embedded words, morphemes, and phrases. A specified format for generating a summary for the digital textual content is identified and probability distribution attributes are generated with respect to target vocabulary of the digital textual content. Content of the digital textual content is replaced with replacement content and an automated digital summary of the digital textual content is generated thereby enabling optimized operational functionality of a recurrent neural network (RNN) encoder-decoder hardware device. A decoded version of the automated digital summary is presented via a specialized graphical user interface.

The invention provides a handwriting real-time digital conversion method and system, and relates to the technical field of handwriting data processing, and the method comprises the steps: collecting handwriting related data in a handwriting process in real time; extracting a handwriting image sequence from the handwriting related data, performing handwriting pixel extraction on each handwriting image in the handwriting image sequence to obtain suspected handwriting pixel data of each handwriting image, and converting each piece of suspected handwriting pixel data into a corresponding suspected handwriting image; performing inter-frame difference extraction on all the suspected handwriting images to obtain a difference handwriting pixel set in the handwriting process, and constructing initial handwriting in the handwriting process through the difference handwriting pixel set; and converting the initial handwriting into a digital text of the handwriting according to pressure data and speed data in the handwriting related data. According to the method, the digital text of the real-time handwriting can be efficiently and accurately generated, so that the conversion delay of the handwriting is reduced.

1. Name of the product of this design: Graphical user interface for calibrated sensor mode of electronic equipment. 2. Purpose of the product of this design: an electronic device whose graphical user interface is used to display information and run programs. 3. The design highlights of this design product lie in the graphical user interface content on the screen. The electronic device is an existing design. In the view, the area of ​​the cross-lines belongs to the content screen, and the content screen itself is not the protected content of this design. The "numbers" and "text content" in the interface are only used to indicate the content area, and the text itself is not the protected content of this design. 4. The picture or photo that best illustrates the design points: Changing state diagram 4. 5. The hardware part of the product is of conventional design, and the rear view, left view, right view, top view and bottom view are omitted. 6. Purpose of the graphical user interface: This design product is used to calibrate the installation position and angle of the sensor. 7. Human-computer interaction method of the graphical user interface: Click the fourth icon module above the main view interface to enter the change state diagram 1, select any number of data in the change state diagram 1 interface to enter the change state diagram 2, click the "Confirm" button in the change state diagram 2 interface to enter the change state diagram 3, when the progress bar in the change state diagram 3 interface starts running, the interface can enter the change state diagram 4 and change state diagram 5 in turn, and when the progress bar reaches 100%, the interface can enter the change state diagram 6.

Automated detection of reasoning in arguments. A training set is generated by: obtaining multiple arguments, each comprising one or more sentences provided as digital text; automatically estimating a probability that each of the arguments includes reasoning, wherein the estimating comprises applying a contextual language model to each of the arguments; automatically labeling as positive examples those of the arguments which have a relatively high probability to include reasoning; and automatically labeling as negative examples those of the arguments which have a relatively low probability to include reasoning. Based on the generated training set, a machine learning classifier is automatically trained to estimate a probability that a new argument includes reasoning. The trained machine learning classifier is applied to the new argument, to estimate a probability that the new argument includes reasoning.