17 results about "E-text" patented technology

The invention discloses a student answer text similarity detection method for artificial intelligence paper marking. The method comprises the following steps: converting a target answer sheet into an electronic text; according to the comprehensive similarity between the student answering text and the question stem text in the electronic text, identifying and positioning similar specific sentences or fragments; comparing the paragraph-level semantic similarity, the key fragment dynamic score, the structural similarity and the keyword coincidence rate according to the student answer text and a model essay text in a preset model essay library, and generating a comprehensive similar risk score; according to a preset multi-level early warning threshold value, outputting a corresponding similar risk early warning level; and presenting the specific sentences or fragments and the same risk early warning level. Therefore, through fusion of question stem similar positioning and model essay multi-dimensional comparison, a comprehensive similar risk score of graded early warning is generated, the transformation from manual low-efficiency screening to intelligent accurate identification is realized, and the paper marking efficiency, the similar detection comprehensiveness and the scoring fairness are remarkably improved.

The application provides a kind of automatic stamping method and system based on invisible watermark, comprising: the electronic text of automatic office unit uploading stamping file and the position information needing stamping;Automatic office unit replaces the electronic text without invisible electronic watermark in process with electronic text;Server informs automatic stamping robot unit to automatically print the electronic text in automatic office unit electronic stamping process;Automatic stamping robot extracts token information in hidden electronic watermark from paper text page by page;If each page token authentication passes, pass through OCR and image matching;Automatic stamping robot stamps information in server through the token of each page text, confirms whether each page text is stamped and where to stamp;Automatic stamping is carried out in the corresponding position of text document, and after stamping is completed, paper document is output.The application can efficiently realize the comparison of paper document and electronic document, and avoid the inconsistency between stamping file and electronic document in approval process.

A text analysis processing for detecting computer-generated text is provided. In some cases, a text-based chat interaction may be initiated and analyzed to determine whether the text-based chat generated by a communicating entity is computer-generated. The text of the chat session may be analyzed to evaluate punctuation, use of emojis, spacing, grammar, words, phrases, and the like to determine a further likelihood of whether the text is computer-generated. A duration of the chat session may be used as a scoring factor. The various probabilities and scores may be combined to provide a composite score.

A method for facilitating electronic textual representation and comparison is disclosed. The method includes receiving, via a graphical user interface, a comparison request that includes a first electronic document and a second electronic document; parsing the first electronic document and the second electronic document to classify textual data; generating, by using the classified textual data, a first tree structure for the first electronic document and a second tree structure for the second electronic document; constructing a first hierarchy dictionary for the first tree structure and a second hierarchy dictionary for the second tree structure; determining differences between the first electronic document and the second electronic document by using the first tree structure, the first hierarchy dictionary, the second tree structure, and the second hierarchy dictionary; and generating graphical representations that depicts the differences and textual representations that summarize the differences.

A text analysis processing for detecting computer-generated text is provided. In some cases, a text-based chat interaction may be initiated and analyzed to determine whether the text-based chat generated by a communicating entity is computer-generated. The text of the chat session may be analyzed to evaluate punctuation, use of emojis, spacing, grammar, words, phrases, and the like to determine a further likelihood of whether the text is computer-generated. A duration of the chat session may be used as a scoring factor. The various probabilities and scores may be combined to provide a composite score.

The present disclosure relates to systems and methods for dynamically creating hyperlinks associated with relevant multimedia content in a computer network. A hyperlink generation module receives an electronic text file from a server. The module searches the text file to identify keywords present in the file. Once the keywords have been identified, a database is queried to identify multimedia content that is related to the keywords. Generally, multimedia content is associated with metadata to enable efficient searching of the multimedia content. Typically, the multimedia content is contextually relevant to both the identified keywords and text file. One or more hyperlinks corresponding to the keywords are then generated and inserted into the text file. The hyperlinks provide pointers to the identified multimedia content. After insertion into the text file, the hyperlinks may be clicked by a user or viewer of the file to retrieve and display the identified multimedia content.

The invention discloses a medical image and electronic text information multi-modal deep learning classification method and system based on an XG-YOLO11 model. The method comprises the steps of performing data preprocessing on medical image and electronic text data; the image takes a pre-trained YOLO11 model as a network architecture, the text information takes a multi-layer perceptron as a basic network architecture, a gradient boosting tree model is fused, and an XG-YOLO11 model is established; a model is used for training, an improved method for reducing feature redundancy is added, and the trained model is used for classifying medical image data and electronic text data to be classified. According to the XG-YOLO11 classification model established by the invention, an existing thought of singly using a deep learning model or a machine learning model is improved, and respective advantages of multiple models are more effectively combined; meanwhile, the features extracted by the deep learning network and the features of the text information have redundancy, and an improved algorithm thought for reducing the feature redundancy is provided.

The invention provides a method and a system for inserting interactive media information in an editable electronic text. The method includes building a user interface to select and upload a plurality of multimedia files from a local device or an online resource. A user can drag a media file into an editing area for file identification, and identification information is obtained. Subsequently, the identification information can be individually configured to be embedded into the target text. In the embedding process, the system provides real-time preview to help the user to check the effect of the multimedia information in the target text. In addition, interaction elements are added to the identification information, so that the interactivity between the user and the multimedia information is enhanced. By improving interactivity, enhancing compatibility, simplifying an editing process, providing real-time feedback, supporting personalized configuration and improving effectiveness of information transmission, the invention provides a more advanced and user-friendly solution aiming at the defects of traditional electronic texts, so that user experience is greatly improved, and diversified requirements of users on information acquisition are met.

1. Name of the product in this design: Braille pen. 2. Purpose of this design: For blind people to scan Braille dots to convert them into speech and to convert Braille text into electronic text during learning. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The invention discloses an electronic text annotation method and device, a storage medium and electronic equipment, and relates to the technical field of artificial intelligence, and the method comprises the steps: extracting to-be-annotated minutiae from a to-be-read text of a user; determining the vocabulary content of the to-be-annotated minutiae from the plurality of read minutiae, wherein the plurality of read minutiae are extracted before the user reads the content corresponding to the plurality of read minutiae; and annotating the to-be-annotated minutiae based on the voku content. Compared with the prior art, the method and the device have the advantages that the vocal contents of the to-be-annotated minutiae can be determined from the read minutiae, so that a user can clearly know the front-back association relationship in the read text on the basis of the annotation when encountering the vocal contents which are associated front and back when reading the text; the situation that the user cannot find the associated content or even cannot read the associated content is avoided, and the reading experience of the user is improved.

The application discloses a signature handwriting identification method based on a multi-modal data joint pre-training mode, collects handwritten electronic text sequence data, positive writing signatures of different signers and corresponding imitated signature sequence data; converts the obtained handwritten electronic text and positive imitated sequence data into corresponding image data representations and carries out data pre-processing; trains a multi-modal data joint classification model by using text sequence data and text image data, obtains a text sequence pre-training encoder and a text image pre-training encoder; carries out fine-tuning training on signature sequence data or signature image data with authenticity labels based on the text sequence pre-training encoder or the text image pre-training encoder to obtain corresponding signature sequence feature extractors or signature image feature extractors; extracts feature vectors according to corresponding signature feature extractors according to the modal of a to-be-detected sample, and compares the feature vectors with reserved sample features to determine authenticity. The application is widely used in places where signatures need to be identified.

The invention discloses a double-level visual guidance method and system for electronic text reading, and relates to the technical field of electronic text processing and display. According to the method, electronic text content and associated audio time sequence information are analyzed, when an audio stream is played, the position of a current pronunciation character is synchronously and dynamically indicated, and a text unit containing the character is subjected to visual enhancement display. According to the method, the user can follow the text content more clearly and accurately while listening to the electronic text for reading, the understanding and perception effects of the user on the text are improved, and the method is suitable for various electronic reading devices and software.

The application discloses an electronic text desensitization method and device, a computing device and a storage medium. The method comprises the following steps: analyzing an electronic text to obtain a sentence set containing multiple sentences, and word segmentation and word vectors corresponding to the word segmentation of any sentence in the sentence set; wherein the sentence set comprises a target sentence and a replacement candidate sentence; for any sentence in the sentence set, identifying an entity contained in the sentence, determining the word segmentation corresponding to the entity as entity word segmentation, and determining the word vector corresponding to the entity word segmentation as an entity word vector; determining an entity-related word vector corresponding to the entity word vector of any sentence; obtaining a privacy word segmentation corresponding to the target sentence and an entity-related word segmentation corresponding to the target sentence in the replacement candidate sentence according to the entity-related word vector; and performing desensitization replacement processing on the privacy word segmentation of the target sentence by using the entity-related word segmentation in the replacement candidate sentence to obtain a desensitized target sentence.

An object of the system according to the embodiment is to enable a person with weak eyesight to efficiently read an electronic document on a PC.SOLUTION: A system according to an embodiment includes an electronic sentence analysis unit and an automatic voice generation unit. The electronic document analysis part analyzes an electronic document displayed on a PC. An automatic voice generation part reads the contents of the electronic sentence analyzed by the electronic sentence analysis part by automatic voice.SELECTED DRAWING: Figure 1

List-based entity name detection implementations are described that detect entity names in electronic textural documents. In one implementation, unknown entity names are detected. In another implementation, ambiguous entity names are detected and disambiguated. In yet another implementation, generic entity names are detected and associated with an applicable species entity name.

A process includes receiving instruction to provide an electronic text document to a plurality of users and a security instruction. In response to the security instruction, the process generates a respective copy of the electronic text document for each user. Each respective copy of the electronic text document is associated with a user identifier of that user and each respective copy includes a respective unique identifier based on a change in presentation of at least one of at least one character of text or at least one image included in the electronic text document. Each copy of the electronic text document having a unique identifier is provided to the user associated with the user identifier associated with that respective copy of the electronic text document. A mapping of each user identifier to the respective unique identifier for the respective copy of the electronic text document is stored in storage.

The invention relates to a method for providing background music to a vehicle occupant 7 reading an electronically provided text in a vehicle 1, in which a context-specific soundtrack is played for the vehicle occupant 7 in the vehicle 1 depending on a reading position in an electronically provided text. In a method that can be implemented in a more user-friendly way, the context-specific soundtrack to be played over the electronically provided text or text segment is generated by artificial intelligence.