21 results about "Lexical database" patented technology

The invention relates to the technical field of vocabulary data, in particular to a construction method of a bilingual vocabulary data knowledge graph. The method comprises the following steps: acquiring a vocabulary database; performing data vocabulary preprocessing on the vocabulary database to obtain unstructured vocabulary data; performing nested relationship extraction according to the unstructured vocabulary data to obtain semi-structured vocabulary data; performing label analysis on the semi-structured vocabulary data to obtain initial vocabulary data; performing context coding on the initial vocabulary data by using a preset BERT model to obtain a vocabulary embedding vector; therefore, by introducing a multi-step collaborative mechanism of context coding, cross-language alignment and graph semantic mapping, the technical problems of incomplete structure, semantic disjunction, poor language transformation ability and the like of a traditional vocabulary construction method are solved, and the automatic construction ability and expression depth of a multi-language semantic knowledge system are improved.

The invention provides a hearing screening system suitable for rural old people, and belongs to the technical field of data processing, and the system comprises a data collection module which collects voice and determines a comprehensive data set; the equipment calibration module is used for determining an audio output parameter of the hardware equipment based on the hardware equipment characteristics in combination with the hardware equipment characteristics, and calibrating the hardware equipment; the parameter determination module is used for determining voice interaction parameters; the hearing test module is used for generating an audiogram; the preliminary judgment module is used for analyzing the audiogram and determining a preliminary judgment result; and the result determination module is used for selecting vocabularies from a preset vocabulary database and a dialect voice database, playing high-frequency audios corresponding to the vocabularies on the calibrated hardware equipment, obtaining user feedback and determining an optimization judgment result in combination with the vocabularies and the dialect voice database. The method has the advantages of individuation, accuracy and high efficiency, is low in cost, is especially suitable for hearing screening requirements of rural old people, and improves the universality and accuracy of screening.

Embodiments of the present disclosure provide systems and methods for performing text extraction from an image including textual data. The method performed by a processor includes extracting machine-readable textual data from the image. The machine-readable textual data includes one or more words. The method includes comparing each of the one or more words with a dataset including a domain lexicon database and a language dictionary database to determine a first set of words and a second set of words. The first set of words is words successfully matching with words available in the dataset, and the second set of words is words with no successful match with words available in the dataset. Further, the method includes splitting at least one word of the second set of words into two or more words to determine a third set of words and generating a textual output associated with the image.

The present invention relates to an LLM text processing method, belonging to the technical field of text processing. The method includes: obtaining input question information; inputting the input question information into a word segmentation database to output question words; inputting the question words into a preset vocabulary database to output synonymous words, mutually exclusive words, and abbreviated words, and defining the question words, synonymous words, mutually exclusive words, and abbreviated words as query words; outputting final question information according to the query words; using a preliminary retrieval method according to the final question information to find out the reference answer information and the corresponding path; inputting the reference answer information and the path into a priority database to match the priority; determining the preliminary retrieval answer information from the matched priority; using a refined retrieval method according to the preliminary retrieval answer information to find out the refined retrieval answer information; taking the refined retrieval answer information as the final answer text and uploading and displaying it. This application has the effect of improving the accuracy of LLM retrieval.

A method for zero-shot event extraction, performed by a computer device. The method includes training a context encoder, a first definition encoder, and a second definition encoder with auto extracted context-definition alignment data; retrieving a plurality of verbal synsets from a lexical database; refining a representation model based on the context-definition alignment data and the plurality of verbal synsets; encoding a plurality of candidate event type definitions; encoding the refined representation model with the trained context encoder; and determining whether the encoded representation model belongs to one of the plurality of candidate event type definitions based on a cosine similarity between the encoded representation model, the trained context encoder, the first trained definition encoder, and the second trained definition encoder.

Embodiments of the present disclosure provide systems and methods for performing text extraction from an image including text data. A method performed by a processor includes extracting machine-readable text data from an image. The machine-readable text data includes one or more words. The method includes comparing each of the one or more words to a data set including a domain vocabulary database and a language dictionary database to determine a first set of words and a second set of words. The first set of words is words that successfully match available words in the dataset, and the second set of words is words that do not successfully match available words in the dataset. Further, the method includes splitting at least one word in the second set of words into two or more words to determine a third set of words and generating a textual output associated with the image.

The invention discloses a Chinese knowledge text word segmentation method and question and answer method, and the method comprises the steps: obtaining a Chinese knowledge corpus material corresponding to a business type, and segmenting the Chinese knowledge corpus material to obtain initial text fragments; for each initial text fragment, performing vocabulary extraction on the initial text fragment according to a pre-generated template vocabulary database to obtain template vocabularies in the initial text fragment; extracting non-template vocabularies according to the template vocabularies in the initial text fragment, and analyzing the non-template vocabularies to determine a professional vocabulary corpus; for each specialized vocabulary corpus, constructing a context relation chain based on the specialized vocabulary corpus, and merging the specialized vocabulary corpus according to nodes in the context relation chain to generate segmented vocabularies; the non-template vocabularies in the initial text fragment are merged according to the word segmentation vocabularies, and the word segmentation result of the initial text fragment is determined based on the merging result and the template vocabularies, so that the problem of inaccurate word segmentation of the Chinese text corpus is solved, and the word segmentation accuracy is improved.

The present disclosure provides a method and apparatus for constructing a thesaurus, relating to the field of computer technologies, and specifically to the fields of big data and data processing technologies. The specific implementation solution is as follows: First, obtain a set of historical samples, where the set of historical samples includes a plurality of first historical samples for constructing the thesaurus. The first historical samples include first identification information and first tag information for indicating whether a predefined event has occurred. Then, perform word segmentation processing on the first historical information corresponding to the first identification information to obtain a plurality of first words corresponding to the first identification information. After that, based on the first tag information corresponding to the first identification information, calculate the probability information corresponding to the plurality of first words. Finally, based on the plurality of first words and the probability information corresponding to the plurality of first words, construct a thesaurus for indicating the occurrence of a predefined event, which can determine a thesaurus for indicating the occurrence of a predefined event based on the first historical information of the first identification information in the set of historical samples.

The invention relates to an LLM text processing method, and relates to the technical field of text processing, and the method comprises the following steps: obtaining input question information; inputting the input question information into a word segmentation database to output question vocabularies; inputting the question vocabularies into a preset vocabulary database to output synonym sets, mutually exclusive vocabularies and thumbnail vocabularies, and defining the question vocabularies, the synonym sets, the mutually exclusive vocabularies and the thumbnail vocabularies as inquiry vocabularies; outputting final question information according to the inquiry vocabulary; according to the final question information, searching reference answer information and a corresponding path through an initial check method; inputting the reference answer information and the path into a priority database to match a priority; determining initial check answer information from the matched priorities; according to the initial inspection answer information, fine inspection answer information is found out through a fine inspection method; and uploading and displaying the fine inspection answer information as a final answer text. The method has the effect of improving the accuracy of LLM retrieval.

The present invention provides a data processing method and system capable of improving efficiency of Chinese vocabulary learning. The method comprises: a data storage unit storing a vocabulary database related to Chinese language learning; segmenting each word into two or more sub-words; binding each sub-word to a balloon graphic, and assigning a color to the balloon; displaying four or more balloons on a client display screen, wherein one sub-word is displayed on each balloon, and the position of the balloon in the screen changes randomly; detecting an instruction for dragging one balloon in the client display screen so that the one balloon at least partially overlaps another balloon; upon detection of said instruction, indicating that phrase matching is performed on the sub-words bound to the selected balloons; and traversing the data storage unit, if there is a corresponding phrase in the data storage unit, indicating that the matching is successful, removing the balloons from the client display screen, and displaying the phrase in a set area of the client display screen, otherwise, retaining the balloons on the client display screen until all balloons in the client display screen are removed.

The embodiment of the invention provides a construction method of a vocabulary database. Determining a parent set corresponding to the child set of each age group, feeding back whether each vocabulary in the first data set belongs to the vocabulary capable of being recognized by the corresponding child or not by parents according to the cognitive performance of the corresponding child, and adding the vocabulary into a second data set corresponding to the age group; respectively using the second data set to generate speech ability test questions of the children of the corresponding age groups; and for a tested vocabulary, adding the vocabulary into the target data set corresponding to the age group of which the test accuracy is higher than the target accuracy, and constructing a vocabulary database. By adopting the scheme provided by the invention, a vocabulary testing tool related to the language ability of the Chinese children can be well established.

The invention relates to a legal translation method and system based on a neural network, and is applied to the technical field of legal translations, and the method comprises the steps: receiving a to-be-translated legal document, preprocessing the to-be-translated legal document, and obtaining a to-be-translated document; mapping the to-be-translated literature with a preset vocabulary database, and determining an unambiguous clear vocabulary and a multi-meaning complex-meaning vocabulary; performing association degree dynamic matching on the meaning of the clear vocabulary and the meaning of the remeaning vocabulary according to a preset language model, and determining an optimal vocabulary meaning corresponding to the remeaning vocabulary; and according to a preset functional verification model, carrying out integration verification on the clear vocabulary and the complex-meaning vocabulary, and outputting a translated document.

The invention relates to the technical field of natural language processing, and discloses a text translation method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a to-be-translated text, segmenting the to-be-translated text, and obtaining a plurality of segmentation objects corresponding to the to-be-translated text; coding each segmented object to obtain a segmented object coding vector of each segmented object; predicting a translation vocabulary of the coding vector of each segmented object to obtain a translation vocabulary prediction result of each segmented object; determining domain vocabularies in the translation vocabulary prediction result based on the translation vocabulary prediction result and a preset domain vocabulary database; and outputting the translated text of the to-be-translated text based on the translated vocabulary prediction result and the domain vocabulary, thereby improving the vocabulary translation accuracy.

A computing device for translating words into a target language includes a computing module for identifying known words in a set of words that have a known translation into the target language, translating said known words into the target language to obtain a combined set of words, determining high-frequency unknown words in the target language in the combined set of words and forming language pairs based on the high-frequency unknown words and their corresponding translations into the target language, and a user interface module for enabling the user to translate the output word, wherein the computing module further checks the word translation for correctness and adds the language pair corresponding to the checked word to a vocabulary database if the indicated word translation is correct.

The present application provides a search method and device. The method includes: receiving a search term input by a user; parsing the search term to obtain multiple parsed terms; determining the return result corresponding to each parsed term based on the multiple parsed terms and a term database, wherein the term database includes: a general term database, a historical selection database, and an abnormal term database, wherein the historical selection database includes terms previously selected by the user, and the abnormal term database includes terms that do not exist in the general term database and the historical selection database; and outputting the return results corresponding to the multiple parsed terms. This can avoid the problem of unsatisfactory search results when the search term cannot accurately describe the content that the user wants to search for.

Semantic frame identification involves associating identified target words in the sentential context of their natural language source with semantic frames from a frame lexical database. The disclosed invention leverages the CapsNet architecture for improved semantic frame identification of a target word in a natural language input. This includes deriving the features of a target word identified in the sentence and extracting the features of the word units and the thematic words around the target word. Through dynamic routing of capsules, the CapsNet is able to filter the candidate frames for the target word to reduce the search space and apply the CapsNet prediction to identify a frame from a frame lexical database.

This invention discloses a classification prediction method driven by label information enhancement and strong negative samples. The method comprises the following steps: first, constructing high-quality text by truncation of text and matching the content of a workbook; second, considering the informativeness of sentiment labels, using a vocabulary database and a professional vocabulary to enrich the sentiment label representation; third, using strong negative sampling to distinguish each text from strong negative samples; and finally, using a prediction loss function that incorporates sentiment label information and a contrastive loss function that incorporates strong negative sampling to ensure model accuracy. This method integrates text truncation, sentiment label information enhancement, and strong negative sampling to improve the accuracy of classification prediction.

The invention provides a business system optimization method and device and electronic equipment, and the method comprises the steps: constructing a vocabulary database which at least comprises professional vocabularies, emotion vocabularies and modification vocabularies; a text input by a user is obtained, the vocabulary database is matched with the text input by the user, target professional vocabularies, target emotion vocabularies and target modification vocabularies in the text input by the user are extracted, a service system corresponding to the target professional vocabularies is determined, and the service system is used for handling financial services; obtaining the emotion intensity of the target emotion vocabulary and the modification intensity of the target modification vocabulary, determining the emotion of the user according to the emotion intensity and the modification intensity, and optimizing the service system according to the emotion of the user, so that the optimized service system meets the requirements of the user. Through the method, the user emotion can be accurately determined, so that the service system can be optimized according to the user emotion, and the service system can better meet the requirements of the user.

A computer server system and method are disclosed for personalization and customization of network search results and rankings, such as for Internet searching. A representative server system comprises: a network interface to receive a query from a user and transmit return queries and search results; a data storage device having a first, lexical database having one or more compilations and templates; and one or more processors configured to access the first database and search a selected compilation using the query to generate initial search results; to comparatively score each selected parsed phrase of the initial search results, for each classification of a selected template and a selected compilation, and to output initial and final search results arranged according to the classifications and the predetermined order of the template. A representative embodiment may also include use of a second, semantic database having multi-dimensional vectors corresponding to parsed phrases, paragraphs, or clauses.

This invention falls within the field of electronics, computer science, and artificial intelligence related to medical conditions and disability. The invention aims to address the needs of people with disabilities or vulnerabilities, such as the blind, mute, or ill, enabling them to ask questions and receive alerts in natural language, even while sleeping, regarding health variables related to the heart, lungs, and temperature. This information can be accessed in real time without physical contact, internet access, or electricity. It is particularly useful for people living in remote, vulnerable areas without access to these services, or during emergencies such as power outages and weather events that disrupt public grid power or internet or artificial intelligence services for diagnosing and monitoring vital functions and medical conditions.To solve the problem, the Device for medical assistance and inclusion of vulnerable people in natural language comprises a sound sensor (7) connected to a natural language processing unit (4) which is connected to a database of words (8) related to medical emergencies, where the natural language processing unit (4) is configured as a means to transform speech into text and is connected to a millimeter wave processor (2) configured to obtain variables of heart rate, respiration and body movement among a plurality of other variables.

The invention relates to the technical field of data processing, and provides a text conversion method and device, electronic equipment and a computer readable storage medium, and the method comprises the steps: obtaining a to-be-converted text; performing query processing on a preset vocabulary database according to the to-be-converted text to obtain a plurality of original word roots; screening a plurality of target roots from the plurality of original roots according to the root popularity of the original roots; performing text division processing on the to-be-converted text according to the plurality of target roots to obtain a plurality of sub-texts; and performing text conversion processing on the plurality of sub-texts according to the conversion texts corresponding to the plurality of target roots to obtain text conversion information. By means of the technical scheme, intelligent text conversion processing can be achieved, the text conversion efficiency is improved, and the text conversion quality is improved.