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138 results about "Word identification" patented technology

Word Identification. Word identification refers to the use of phonics to decode a word. Without word identification, every word would have to be recognized by sight to be read.

Biomedicine event trigger word identification method based on characteristic automatic learning

The invention relates to the technical field of biomedicine, and relates to a biomedicine event trigger word identification method based on characteristic automatic learning. The biomedicine event trigger word identification method comprises the following steps of 1, data pre-processing; 2, construction of an event trigger word dictionary; 3, construction of candidate trigger word examples; 4, characteristic learning by means of a convolutional neural network model; 5, training by means of a neural network model; and 6, classification of event trigger words. The biomedicine event trigger word identification method is advantaged in that 1, complex preprocessing to data is simplified, and tedious steps for carrying out a characteristic design by people are saved; 2, domain knowledge is introduced, and a lot of external resources such as unlabeled linguistic data are effectively utilized; 3, characteristic automatic learning is carried out by means of a convolutional neural network, manual intervention is reduced, sentence level characteristics in a deeper level can be excavated and explored, through the fusion of local characteristics, implicit global characteristics are discovered, and the category of trigger words can be identified; and 4, a better experiment result is obtained in MLEE linguistic data, and the whole performance on event trigger word detection is improved.
Owner:DALIAN UNIV OF TECH

Event extraction system and method oriented to open domain

The invention relates to an event extraction system and method oriented to an open domain. The system comprises a preprocessing module, a trigger word identification module, an event parameter identification module, an event atlas analysis module and an event extraction display module, wherein the preprocessing module preprocesses original data information; the trigger word identification module carries out trigger word identification on the basis of a convolutional neural network; the event parameter identification module carries out event parameter identification on the basis of a graph model, the extraction work of an event parameter is converted into a specific graph segmentation problem, and the event parameter is obtained through segmentation; the event atlas analysis module analyzes trigger word identification results and event parameter identification results to obtain the same kind of events; and the event extraction display module carries out visual display on an analysis result so as to bring convenience for users to obtain information. By use of the system, the difficulty that news information can be quickly obtained under a big-data environment is solved, and the user can obtain a news event related to a keyword according to the keyword input on the own so as to provide great convenience for information acquisition.
Owner:BEIHANG UNIV

Biomedical event trigger word identification method based on syntactic word vector

ActiveCN104965819AImprove generalization abilityImprove trigger word recognition performanceSpecial data processing applicationsWord identificationData set
The invention relates to an identification method, in particular to a biomedical event trigger word identification method based on a syntactic word vector. The biomedical event trigger word identification method comprises the following steps of: 1, pre-processing un-marked data; 2, carrying out word vector training based on syntactic context information; 3, constructing a candidate trigger word dictionary; 4, constructing a trigger word semantic feature vector; 5, training a deep learning model; and 6, identifying a biomedical event trigger word. According to the biomedical event trigger word identification method, syntactic information of the trigger word is precisely acquired by utilizing a larger number of trained word vectors capable of obtaining unmarked data, and input characteristic dimension is effectively reduced; concealed features among the input features are leaned by utilizing the deep learning model, so that the input features are sorted more precisely; and finally, fine adjustment is carried out on word vector information in a training process, so that the word vector information is more suitable for a data set, and thus, the generalization ability and the trigger word identification word of the model are effectively improved.
Owner:DALIAN UNIV OF TECH

Method for automatically correcting identification error of repeated words in Chinese pronunciation identification

The invention provides a method for automatically correcting an identification error of repeated words in Chinese pronunciation identification. The method comprises the following steps of: (1) performing similarity matching on word confusion networks which are obtained after identification of each sentence, word groups in a word group library and intermediate identification results, and searching the repeated word groups, wherein each word confusion network is a set of all possible identification results and comprises an optimum identification result, namely the original optimum identification result, and the intermediate identification result which corresponds to each word in the optimum identification result, and the word group library comprises the word groups and the intermediate identification results which correspond to the word groups; (2) according to word group information which is obtained by searching, re-calculating a similar probability value and a word identification probability value; (3) according to a new probability value, sorting the word confusion networks according to the size of the probability value; and (4) replacing the optimum identification results and the intermediate identification results of the word confusion networks by using a sorting result. The method has the advantages that: by using experience knowledge in the corrected identification result, the identification error of the repeated words in the current identification sentence is automatically corrected, so the correction efficiency and correction speed of the identification error are improved.
Owner:INST OF COMPUTING TECH CHINESE ACAD OF SCI

Method and terminal for rectifying deviation of file

ActiveCN101887521AImprove recognition accuracyOvercome the defect of relatively low recognition rateCharacter and pattern recognitionWord identificationText categorization
The invention relates to a method and a terminal for rectifying deviation of a file. The terminal comprises an image acquisition and processing module, an image inclination angle detection module and an image deviation rectifying and correcting module, wherein the image acquisition and processing module takes a picture of a file through a camera, acquires an image and processes the file image to obtain a black and white two-dimensional image; the image inclination angle detection module detects the inclination angle of the file image by an image inclination angle detection algorithm; and the image deviation rectifying and correcting module performs deviation rectifying on the image of a visiting card to obtain a corrected image of the visiting card according to the inclination angle of the image of the visiting card detected by the image inclination angle detection module. According to the technical scheme, the deviation of the file image is finally rectified through OCR word identification, text category identification and information checking, amending and authentication, so the method and the terminal overcome the defect of low scan information identification rate existing in the prior art and improve the identification accuracy of the information.
Owner:ZTE CORP

System and method for high concurrent ticket identification based on deep learning

The present invention discloses a system and a method for high concurrent ticket identification based on deep learning. According to the invention, a unified API interface and a ticket classification system are combined so that the system has high compatibility with any ticket input. The combination of an Nginx load balancing server, an HTTP SERVER cluster, a queue server and a GPU ticket identification cluster makes the ticket recognition system high concurrent. The combination of a template adaptation and sequence location system and word identification system of deep learning makes the ticket recognition system easy to operate. The combination of the ticket classification system, the template adaptation and sequence location system, the word identification system of deep learning, the ticket field matching semantic analysis system, the ticket subclass extraction semantic analysis system and the service field content correction semantic analysis system makes the ticket identification system have a high identification rate. Compared with the traditional ticket identification system, the system and the method of the invention have the advantages of good compatibility, high concurrency, easy operability and high identification rate.
Owner:SICHUAN CHANGHONG ELECTRIC CO LTD

Chinese text keyword extraction method based on document theme structures and semantics

The invention discloses a Chinese text keyword extraction method based on document theme structures and semantics, and relates to keyword extraction. The method includes the steps: text preprocessing;Chinese segmentation and part-of-speech tagging; stop word filtering and part-of-speech filtering; keyword extraction. The basic conception of text keyword extraction, Chinese segmentation and English segmentation differences and a common Chinese text keyword extraction method are introduced. A method based on the document theme structures and a method based on semantics are researched, and the principle and an existing implementation scheme are analyzed. In order to overcome difficulty in new word identification in Chinese segmentation, Chinese segmentation effects are continuously improvedby the aid of a dynamically updated segmentation dictionary. The method based on the document theme structures is improved, and global keywords are extracted. Semantic similarities of Chinese words are taken into account, and an algorithm is further improved. The improved algorithm is verified in a self-built data set, good results are acquired by verification experiments and comparison experiments, and keyword extraction effects can be improved by the improved algorithm.
Owner:厦门纵横集团科技股份有限公司

Isolation word identification method based on double-layer GMM structure and VTS feature compensation

The invention discloses an isolation word identification method based on a double-layer GMM structure and VTS feature compensation. The method comprises a training stage and an identifying stage. In the training stage, by voice feature extracting under a pure environment, two GMM training models and an HMM training models are obtained. Each GMM model comprises a GMM1 model containing a small number of Gauss mixing units and a GMM2 model containing a large number of Gauss mixing units. During a noise estimation process at a vector Taylor series (VTS) feature compensation stage, the GMM1 model is used for obtaining the mean value and the variance of noise, a GMM2 model is used for obtaining a pure feature parameters by mapping, and matching with the HMM module is carried out to obtain the final identification results. Compared with an isolation word identification algorithm based on a single GMM model and VTS feature compensation, under the situation that the error recognition rate is not changed basically, noise mean value and variance estimating time is shortened by 90%, feature compensation overall time is shortened by 30%-50%, and calculated quantity of the isolation word identification algorithm based on the VTS feature compensation is effectively lowered.
Owner:SOUTHEAST UNIV
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