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39 results about "Lexical semantics" patented technology
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Lexical semantics (also known as lexicosemantics), is a subfield of linguistic semantics. The units of analysis in lexical semantics are lexical units which include not only words but also sub-words or sub-units such as affixes and even compound words and phrases. Lexical units make up the catalogue of words in a language, the lexicon. Lexical semantics looks at how the meaning of the lexical units correlates with the structure of the language or syntax. This is referred to as syntax-semantic interface.
Probabilistic method for natural language processing and for encoding free-text data into a medical database by utilizing a Bayesian network to perform spell checking of words
InactiveUS6292771B1Improve accuracyAccurate identificationSemantic analysisText processingProbit modelProbabilistic method
A natural language understanding system is described which provides for the generation of concept codes from free-text medical data. A probabilistic model of lexical semantics, in the preferred embodiment of the invention implemented by means of a Bayesian network, is used to determine the most probable concept or meaning associated with a sentence or phrase. The inventive method and system includes the steps of checking for synonyms, checking spelling, performing syntactic parsing, transforming text to its "deep" or semantic form, and performing a semantic analysis based on a probabilistic model of lexical semantics. In the preferred embodiment of the invention, spell checking and transformational processing as well as semantic analysis make use of semantic probabilistic determinations.
Owner:INTERMOUNTAIN INTELLECTUAL ASSET MANAGEMENT LLC
Probabilistic system for natural language processing
InactiveUS20020128816A1Free-text documents easierLess-expensive to produceSemantic analysisText processingProbit modelNatural language understanding
A natural language understanding system is described to provide generation of concept codes from free-text medical data. A probabilistic model of lexical semantics, is implemented by means of a Bayesian network, and is used to determine the most probable concept or meaning associated with a sentence or phrase. The inventive method and system includes the steps of checking for synonyms, checking spelling, performing syntactic parsing, transforming text to its "deep" or semantic form, and performing a semantic analysis based on a probabilistic model of lexical semantics.
Owner:INTERMOUNTAIN INTELLECTUAL ASSET MANAGEMENT LLC
Entity relationship extracting method of Zang language
ActiveCN104809176AExtraction implementationImplement classificationSpecial data processing applicationsFeature vectorAlgorithm
The invention relates to an entity relationship extracting method of the Zang language. The method comprises the following steps: extracting training linguistic data from the Zang-Chinese text linguistic data information; constructing a Zang word vector model; acquiring an entity relationship characteristic vector from the Zang word vector model; using the entity relationship characteristic vector as an input to construct an entity relationship classification model based on a neural network; and applying multiple layers of characteristic extractions to the entity relationship characteristic vector, thereby finally acquiring a Zang language entity relationship classification. The extraction of the Zang language entity relationship is achieved by constructing the Zang word vector model, researching and solving lexical semantic characteristics and sentence characteristic vector expression methods of the Zang language entity relationship, and further constructing the Zang language entity relationship classification model, accordingly increasing the accuracy in the Zang language entity relationship classification, and providing technical supports and services to the researches in the fields of the Zang language knowledge mapping, question-answering system, information extraction, information search, and the like.
Owner:MINZU UNIVERSITY OF CHINA
Lexical semantic structure
A lexical semantic structure for modeling semantics of a natural language input on a computer is described. A set of lexical semantic categories is selected to model content of the natural language input. A methodology associates content of the natural language input to one or more categories of the set of lexical semantic categories.
Owner:MICROSOFT TECH LICENSING LLC
Systems and methods for results list navigation using semantic componential-gradient processing techniques
InactiveUS20080243777A1Digital data processing detailsSpecial data processing applicationsResult listInformation retrieval
Systems ana methods are provided for organizing and presenting large search results lists using lexical semantic componential-gradient processing techniques to dynamically organize search results into a gradable list of context rich semantic components, which is presented to a user under a gradient as a constrained set of choices to thereby facilitate user navigation of the search results.
Owner:STEWART OSAMUYIMEN THOMPSON +1
Extraction method of semantic relation between Chinese entities
ActiveCN102799577AReduce in quantityReduce dependencySpecial data processing applicationsRelation classificationNODAL
The invention discloses an extraction method of a semantic relation between Chinese entities. The extraction method comprises the following steps of: carrying out syntactic analysis on natural statements to determine a complete syntactic tree of the natural statements; extracting a shortest path containing tree between two Chinese entities from the complete syntactic tree; extracting a path verb nearest to a second Chinese entity from the shortest path containing tree; respectively acquiring the semantic information of the two Chinese entities and the path verb; adding the three acquired semantic information into a root node of the shortest path containing tree according to a preset rule to determine the expanded shortest path containing tree to be a natural statement relation tree; and carrying out relation classification on the relation tree by utilizing a prestored classification model. According to the extraction method of the semantic relation between Chinese entities, which is disclosed by the invention, the relation tree contains abundant structured information and lexical semantic information and has better generality and semantic relation extraction overall performance, the dependence degree of a large-scale corpus is relieved, and meanwhile, the calculated amount of the system is lower.
Owner:SUZHOU UNIV
Lexical semantic structure
A lexical semantic structure for modeling semantics of a natural language input on a computer is described. A set of lexical semantic categories is selected to model content of the natural language input. A methodology associates content of the natural language input to one or more categories of the set of lexical semantic categories.
Owner:MICROSOFT TECH LICENSING LLC
Natural language knowledge acquisition method based on semantic matching driving
InactiveCN102945230ASpecial data processing applicationsSemantic matchingKnowledge acquisition method
The utility model discloses a natural language knowledge acquisition method based on semantic matching driving. The natural language knowledge acquisition method comprises the following steps: (1) defining a semantic model for natural language processing; (2) defining a representing method of lexical semantic; (3) defining semantic matching relations among the lexicons; (4) defining a processing method of statements; and (5) transforming analysis results into knowledge points. According to the natural language knowledge acquisition method based on the semantic matching driving, an analysis scheme better accordant with semantic logics can be selected as the final analysis result from multiple grammatical analysis schemes according to semantic matching values by adopting semantic matching information to cooperate with common syntax rules in a small quantity of natural languages. Through the adoption of the method, the natural language statement analysis can be carried out and knowledge contained in the statements of the natural languages can be acquired. Experiments indicate that the method has higher feasibility.
Owner:ANYANG NORMAL UNIV
Method and system for mining Chinese event information
ActiveCN103617280AReduce excavation costsImprove digging efficiencySpecial data processing applicationsEvent typeIterative method
The invention discloses a method and system for mining Chinese event information. The method includes the steps of defining an event sample model based on the mining requirement, instantiating the event sample model to obtain a seed event, taking the seed event as the foundation of an event mined from an original text, conducting preprocessing on the original text to obtain a candidate template set, conducting information labeling on the seed event, processing the seed event on the basis of labeling information to obtain a seed template set, then, processing the candidate template set through an iterative method according to the grade scores of candidate templates and the semantic similarity between the candidate templates and seed templates so that an event mining anchor set can be obtained, and obtaining the event types corresponding to mining event anchors according to the lexical semantic similarity between each event mining anchor in the event mining anchor set and any seed event anchor in the seed event set. The aim of mining the Chinese event information from the original text can be achieved only by labeling a small amount of samples, namely, the seed events, and the mining cost is reduced.
Owner:苏州大数据有限公司 +2
Text similarity measuring method based on semantic analysis and semantic relation network
The invention discloses a text similarity measuring method based on semantic analysis and a semantic relation network. First, two texts are input and are preprocessed, and a preprocessed result is a collection of vocabularies; second, the lexical semantic similarity of the preprocessed result of the two texts is calculated, and the semantic relation network in constructed according to a calculation result; third, flow medium numerical values of nodes in the semantic relation network are respectively calculated, and characteristic collection of the two texts is obtained; fourth, a bipartite graph is constructed according to the characteristic collection of the two texts, and a path weight number between two parts of the bipartite graph is set; fifth, the similarity between the two texts is calculated by utilizing a bipartite graph optimal matching method. The text similarity measuring method based on the semantic analysis and the semantic relation network can be used for the technical field of data mining and information retrieval technology such as text clustering and information retrieval. Compared with other existing text similarity calculating methods, the accuracy degree of text similarity calculation is greatly improved.
Owner:SHANDONG ZHONGFU INFORMATION IND
Information monitoring and analyzing system
ActiveCN104809108AEfficient collectionEfficient analysisSpecial data processing applicationsThe InternetWord group
The invention provides an information monitoring and analyzing system. The information monitoring and analyzing system comprises a data preprocessing module and a semantic orientation identification module, wherein the data preprocessing module is used for screening web texts by utilizing positive and negative emotion symbols and extracting a candidate-word set from the screened web texts; the semantic orientation identification module is used for establishing a network of lexical semantic trend values for the candidate-word set obtained from data preprocessing, selecting emotion symbols of which the word frequency in the candidate-word set in an emotion set is higher than the preset value as candidate words, expanding low-frequency words by utilizing a synonym word group, extracting emotion words, and calculating the semantic orientation strength by utilizing the candidate words and the network of lexical semantic trend values so as to realize the semantic orientation recognition of words. Through the adoption of the information monitoring and analyzing system provided by the invention, the multi-dimensional monitoring is performed on the public sentiment of the Internet, and the sensitive information is effectively acquired and analyzed, so that the precision ratio and the recall ratio are increased.
Owner:元力云网络有限公司
Word semantic embedding apparatus and method using lexical semantic network and homograph disambiguating apparatus and method using lexical semantic network and word embedding
ActiveUS20190188263A1Less learning dataShorten study timeSemantic analysisSpeech recognitionWord listAmbiguity
A word semantic embedding apparatus includes: a data storing unit to store a lexical semantic network including word dictionary data and word semantic data; a word list generating unit to extract vocabularies having a predetermined part of speech from the stored word dictionary data and generate a list of words to be learned; a processing data generating unit to bring the generated list of words to be learned and the word semantic data of a word to be learned included in the list of words to be learned from the data storing unit and process the data suitable for word embedding learning to generate processing data; and a word embedding learning unit to learn the word to be learned through the word embedding learning using a learning model formed of an input / output layer and a projection layer with the generated processing data to generate a word vector.
Owner:UNIV OF ULSAN FOUND FOR IND COOPERATION
Chinese-English cross-lingual lexical representation learning method and system based on paraphrase primitives
The invention discloses a Chinese-English cross-language vocabulary representation learning method and system based on paraphrasing primitive words, which represents the vocabulary of Chinese and English languages in vector form in the same vector space, and obtains more accurate word embedding combined with semantic information. Firstly, the set of paraphrasing primitives is obtained by processing the paraphrasing relations in Chinese dictionaries, so that the words in the set of paraphrasing primitives can cover all the lexical semantics in dictionaries. Secondly, all the words in Chinese dictionaries and English dictionaries are represented by the vectorized expressions of the paraphrasing primitives. The vectorized expressions of the paraphrasing primitives are used to express all thewords in the dictionaries. Finally, combining with the context and semantic relationship of Chinese and English corpus, we set certain weights on the expression of paraphrase primitives in vocabularyto obtain more accurate semantic relational word embedding. Compared with the existing word embedding, the invention has the advantages of high word embedding accuracy, strong expansion ability, convenient realization and the like, and can better serve the subsequent natural language processing tasks.
Owner:IOL WUHAN INFORMATION TECH CO LTD
Psycholinguistic evaluation method and system for Chinese aphasia
InactiveCN108113651AIncrease contentDetailed contentSpeech analysisDiagnostic recording/measuringVisual recognitionGlyph
The invention provides a psycholinguistic evaluation method and system for Chinese aphasia. The method comprises performing auditory analysis testing, speech input buffer testing, speech input dictionary testing and lexical semantic testing on a patient in sequence; performing visual discrimination testing, concept semantic testing, lexical semantic testing, speech output dictionary testing and speech motion planning testing on the patient in sequence; sequentially performing glyph visual recognition testing, glyph input dictionary testing, and lexical semantic testing on the patient in sequence; and evaluating and judging evaluation test results. The system includes a main server, a client and a human-computer interaction terminal. The main server includes a database and a listening comprehension evaluation process subsystem, a graph naming evaluation process subsystem, a reading evaluation process subsystem and a test evaluation module. According to the psycholinguistic evaluation method and system for Chinese aphasia, the damage of different properties in aphasia can be determine by evaluation testing, and a therapist can be assisted to accurately locate the damaged part of thebrain region, thereby achieving targeted treatment of aphasia and improving the treatment efficiency.
Owner:汪洁 +1
Text feature extraction method based on semantic analysis
InactiveCN106610949AImprove accuracyImprove use valueNatural language data processingSpecial data processing applicationsFeature extractionInformation gain
The invention provides a text feature extraction method based on semantic analysis. The method comprises the following steps: initializing a text corpus, performing word segmentation and unused word removal processing on texts, clustering the texts according to semantic relevance (the formula is as shown in the specification), constructing a lexical semantic network model graph, obtaining the status and the contribution of a vocabulary in the whole text according to the importance of the vocabulary in a lexical semantic network model, setting a proper importance threshold, and extracting a feature vocabulary vector of the text. Compared with the tradition word frequency-inverse document frequency method, the text feature extraction method provided by the invention has the advantages of having higher accuracy, overcoming the defect that only one category of text features can be extracted by the information gain method, having higher application value, accurately calculating the contribution of different vocabularies to the idea of the text and meanwhile providing good theoretical basis for subsequent text clustering.
Owner:SICHUAN YONGLIAN INFORMATION TECH CO LTD
Semantic ontology creation and vocabulary expansion method for Tibetan language
InactiveCN103473222AImprove processing precisionSpecial data processing applicationsInformation processingMulti language
The invention relates to a method for processing Chinese minority scripts, in particular to a semantic ontology creation and vocabulary expansion method for a Tibetan language. The method comprises the following steps: (1) establishing an upper level ontology on the basis of the Chinese dictionary of the HowNet; (2) expanding conceptual synonyms appearing in the upper level ontology by using definitions in an electronic dictionary; (3) carrying out a conceptual hyponymy mode matching algorithm on the upper level ontology in a multi-language ontology library to expand the concept of the upper level ontology; (4) searching for conceptual synonyms in the expanded ontology; (5) sequencing from higher similarities to lower similarities on the basis of an ontology conceptual lexical semantic similarity algorithm; (6) modifying the sequencing results and editing the ontology. According to the method, the upper level ontology is established on the basis of the Chinese dictionary of the HowNet, levels of different concepts are defined according to a hyponymy in the ontology, and more new semantic words can be obtained on the basis of the hyponymy, so that the vocabulary of the existing Tibetan language ontology is expanded, and the Tibetan language information processing accuracy is increased greatly.
Owner:MINZU UNIVERSITY OF CHINA
Big data processing method based on machine learning
ActiveCN109214004AAdapt to the needs of excavationSemantic analysisNeural architecturesData dredgingSemantic vector
The invention provides a big data processing method based on machine learning, which comprises the following steps: given a retrieval sentence, filtering the words in the initial retrieval by using auniversal stop word list, and reserving meaningful retrieval words; the semantic block model is used to represent the lexical semantic vector. On the basis of semantic vector, cosine similarity is used to find out the closest words from other words for each initial search term, which can be used as extended search terms. The corresponding extended search terms in the initial search are used to replace the original search terms, and the newly generated search term sequence is used as the extended search terms. According to the permutation and combination of the extended search terms, the extended search sentences with different expressions are obtained. The invention improves the parallel frame of the MAPRUDUCE and is better adapted to the needs of text data mining. Aiming at the irregularity of social text, semantic vectors are used to represent and analyze the text data effectively, which is suitable for the analysis and calculation of social text mining of various scales.
Owner:贵州航天云网科技有限公司
Ontology concept-based lexical semantic similarity solving method
InactiveCN106611038AImprove accuracyEnhance reasoning abilitySpecial data processing applicationsMaximum depthDegree of similarity
The invention provides an ontology concept-based lexical semantic similarity solving method, which comprises the steps of mapping to-be-compared words input in a statistical method module into an ontology concept; selecting ontology concepts, with corresponding maximum depths, of the to-be-compared words from an ontology concept module, calculating the distance between the ontology concepts and calculating the most recent common ancestor depth; and finally calculating the similarity between the two to-be-compared words. The ontology concept-based lexical semantic similarity solving method is closer to an empirical value of an expert in quantitative concept; the factors of the distance between the ontology concepts, with the corresponding maximum depths, of the to-be-compared words (c1, c2), the depths and the like are more fully and comprehensively considered, so that the accuracy of the semantic similarity result is greatly improved; and the ontology reasoning effect is better improved.
Owner:SICHUAN YONGLIAN INFORMATION TECH CO LTD
Method for realizing text feature extraction based on improved small-world network model
InactiveCN107038155AImprove accuracyImprove use valueSemantic analysisSpecial data processing applicationsFeature extractionAlgorithm
The invention discloses a method for realizing text feature extraction based on an improved small-world network model. According to the method, a semantic relevancy function is determined according to a Chinese word segmentation preprocessing process and determined vocabulary position weights and word class weights in combination with a (HowNet) two-vocabulary relevancy algorithm and a vocabulary-to-text importance method, wherein the function is subjected to normalization processing, and calculation conditions of values are more standard; and two parameters, namely a density parameter and a weight parameter are set for a lexical semantic network model graph, the two parameters are effectively fused, and an appropriate threshold value is set to extract text feature vocabularies. The method has higher accuracy and overcomes the defect that a traditional method is only suitable for extracting text features of one category; the method has higher application value, contribution degrees of different vocabularies to text thought can be precisely calculated, data processing is more standard, the result error rate is lowered, the constructed lexical semantic network model graph better conforms to the actual condition, and meanwhile a good theoretical basis is provided for subsequent text clustering.
Owner:SICHUAN YONGLIAN INFORMATION TECH CO LTD
Mining and displaying method combining vocabulary matching extraction and semantic classification
PendingCN112860781AIncrease information densitySemantic analysisVisual data miningPattern recognitionCollocation
The invention discloses a mining and displaying method combining vocabulary matching extraction and semantic classification, and belongs to the field of natural language processing and language learning application. The method comprises: extracting and filtering word collocation by using a deep learning-based dependency syntax semantic model and a statistical method; in combination with the sorted word classification and the extracted collocation, calculating a many-to-many collocation matrix; screening, sorting and recombining the collocation words and the word classification according to the collocation density; displaying the finally obtained word classification matching matrix in an m*n or m*n*o card form; and the cards are displayed according to a hierarchical sequence of lexical semantic classification. Through the method, a collocation and vocabulary classification system with more general significance and a many-to-many word classification collocation matrix display form can be obtained, the display form is visual and vivid, the information density is large, and systematic learning of language vocabularies is facilitated through a semantic and pragmatic combination grouping mode.
Owner:陈永朝
Word vector correction method based on semantic relation constraint and computing system
InactiveCN112966523AImprove accuracyImprove correction efficiencySemantic analysisBiological neural network modelsKnowledge sourcesAlgorithm
The invention provides a word vector correction method based on semantic relation constraint and a computing system. The method comprises the following steps: a synonym and antonym constraint set with a symmetric relation and a direct hypernym / hypernym constraint set with an asymmetric relation are extracted as an external knowledge source update word embedding vector from WordNet and Roget semantic dictionaries; and the similarity of the pair of vocabularies can be calculated by randomly inputting two vocabularies of which the similarity needs to be calculated. The vocabulary semantic similarity calculation system comprises an input unit, an initialization unit, a calculation unit and an output unit. According to the method, the existing neural network word embedding vector is updated based on the lexical semantic relationship constraint provided by the external knowledge source so as to be used for lexical semantic similarity calculation. The updating speed and the word embedding vector semantic updating effect are obviously better than those in the prior art, and the accuracy rate in calculating the word semantic similarity is higher.
Owner:SHANDONG JIANZHU UNIV
Improved lexical semantic similarity solution algorithm
InactiveCN106610948AIncrease reflectionMeets requirementsNatural language data processingSpecial data processing applicationsSemantic similarityLexical semantics
The invention provides an improved lexical semantic similarity solution algorithm. On the basis of a successfully initialized statistical method module, a maximum keyword is extracted by comparing context words with the maximum weights of words to be compared and the similarity of the words to be compared, and finally the similarity between the extracted maximum keyword and the words to be compared is calculated to obtain a result. The calculation result of the semantic similarity is basically consistent with actually manually judged semantic similarity; the objective reality is better reflected; and the user demands are better satisfied.
Owner:SICHUAN YONGLIAN INFORMATION TECH CO LTD
Novel method for solving lexical semantic similarity between ontology concepts
InactiveCN106610940AImprove accuracyEnhance reasoning abilitySemantic analysisSpecial data processing applicationsPattern recognitionMaximum depth
The invention provides a novel method for solving the lexical semantic similarity between ontology concepts. The method comprises the steps of calculating the similarity between the ontology concepts, with the maximum depths, of to-be-compared words input into a statistical method module; calculating the word form similarity between the two to-be-compared words, calculating the influence of the most recent common ancestor depth of the two to-be-compared words on the similarity between the two to-be-compared words and constructing an impact factor function; and finally calculating the similarity between the two to-be-compared words. The novel method is closer to an empirical value of an expert in quantitative concept; the factors of the distance between the ontology concepts, with corresponding maximum depths, of the to-be-compared words, the depths, the density and the like are more fully and comprehensively considered, so that the accuracy of the semantic similarity result is greatly improved; the ontology reasoning effect is better improved; better improvement of the accuracy of the word form similarity result and the semantic similarity result between the words is considered; data processing of various influence factors is more standard; and the novel method accords with the practical application effect.
Owner:SICHUAN YONGLIAN INFORMATION TECH CO LTD
New small world network model realization text feature extraction method
InactiveCN107066448AImprove accuracySemantic analysisSpecial data processing applicationsPart of speechFeature extraction
The invention discloses a new small world network model realization text feature extraction method. According to a Chinese word segmentation preprocessing process, position weights and part-of-speech weights of vocabularies are determined; semantic correlation functions defined in the specification are determined by integrating "HowNet"-based two vocabulary correlation algorithms and a method for importance of the vocabularies to a text; herein, the functions are all subjected to normalization processing; value calculation conditions are more normative and stricter; two parameters including a density parameter and an edge weight parameter are set for a lexical semantic network model graph; proper thresholds are set for the parameters; and when the conditions are met, the vocabularies are text feature vocabularies. The method has higher accuracy, overcomes the deficiency that an information gain method is only suitable for extracting a type of text feature, has higher application values, and can accurately calculate contribution degrees of different vocabularies to a text thought; the data processing is more normative; the constructed lexical semantic network model graph better conforms to actual conditions; and a good theoretical basis is provided for subsequent text clustering.
Owner:SICHUAN YONGLIAN INFORMATION TECH CO LTD
Cloud service vertical search charging pile system based on user behaviors
InactiveCN106294625APowerful Computing ServicesImprove computing powerWeb data indexingSemantic analysisInformation analysisThe Internet
The invention discloses a cloud service vertical search charging pile system based on user behaviors. The system comprises an information collection layer, an information analysis layer and a matching layer. The information collection layer comprises a behavior database group, an information module and an internet of things data module. The information analysis layer comprises a behavior big data analysis module and lexical semantic analysis. The matching layer comprises an internet of things data matching module and matching results. The information module comprises user basic information and peripheral information. The behavior big data analysis module comprises data mining and cloud computing. The internet of things data matching module comprises a matching core module and a Solr vertical search engine. The system has the advantages that through utilization of cloud computing, storage and access of big data are supported, the computing service far stronger than that of a single computer is provided, and the effective utilization rate of the existing system computing capability can be greatly improved.
Owner:SUZHOU HONGRAN INFORMATION TECH
Word semantic embedding apparatus and method using lexical semantic network and homograph disambiguating apparatus and method using lexical semantic network and word embedding
ActiveUS10984318B2Less dataShorten study timeSemantic analysisSpeech recognitionPart of speechLearning unit
A word semantic embedding apparatus includes: a data storing unit to store a lexical semantic network including word dictionary data and word semantic data; a word list generating unit to extract vocabularies having a predetermined part of speech from the stored word dictionary data and generate a list of words to be learned; a processing data generating unit to bring the generated list of words to be learned and the word semantic data of a word to be learned included in the list of words to be learned from the data storing unit and process the data suitable for word embedding learning to generate processing data; and a word embedding learning unit to learn the word to be learned through the word embedding learning using a learning model formed of an input / output layer and a projection layer with the generated processing data to generate a word vector.
Owner:UNIV OF ULSAN FOUND FOR IND COOPERATION
A Deep Learning Text Classification Method Integrating Shallow Semantic Representation Vectors
ActiveCN110069632BEfficient use ofEffective trainingSemantic analysisNeural architecturesSemantic vectorSemantic representation
The invention discloses a deep learning text classification method integrating shallow semantic representation vectors. The method includes: first training word embedding vectors on text corpus, and secondly using domain vocabulary dictionary as shallow semantic vocabulary to generate text based on shallow semantic vocabulary A shallow semantic vector representation of each word in the corpus. Next, the weighted splicing of the two word vectors is input into the CNN model as a new word vector for feature extraction and model training to build a text classifier. The invention solves the defect that the big data-driven word vector expression lacks lexical features and knowledge representation, and it is difficult to truly understand the semantic information of the words, so that the model has richer feature expressions and higher classification performance.
Owner:HUAQIAO UNIVERSITY
Text Similarity Measuring Method Based on Semantic Analysis and Semantic Relationship Network
ActiveCN103092828BImprove accuracySpecial data processing applicationsComputational semanticsSemantic network
Owner:SHANDONG ZHONGFU INFORMATION IND
A Chinese event information mining method and system
ActiveCN103617280BReduce excavation costsImprove digging efficiencySpecial data processing applicationsEvent typeInformation mining
The invention discloses a method and system for mining Chinese event information. The method includes the steps of defining an event sample model based on the mining requirement, instantiating the event sample model to obtain a seed event, taking the seed event as the foundation of an event mined from an original text, conducting preprocessing on the original text to obtain a candidate template set, conducting information labeling on the seed event, processing the seed event on the basis of labeling information to obtain a seed template set, then, processing the candidate template set through an iterative method according to the grade scores of candidate templates and the semantic similarity between the candidate templates and seed templates so that an event mining anchor set can be obtained, and obtaining the event types corresponding to mining event anchors according to the lexical semantic similarity between each event mining anchor in the event mining anchor set and any seed event anchor in the seed event set. The aim of mining the Chinese event information from the original text can be achieved only by labeling a small amount of samples, namely, the seed events, and the mining cost is reduced.
Owner:苏州市大数据集团有限公司 +2
Big data processing method based on machine learning
ActiveCN109214004BAdapt to the needs of excavationSemantic analysisNeural architecturesData dredgingSemantic vector
Owner:贵州航天云网科技有限公司
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