30 results about "Analytic language" patented technology

A method of, and system for, generating a sentence from a semantic representation maps the semantic representation to an unordered set of syntactic nodes. Simplified generation grammar rules and statistical goodness measure values from a corresponding analysis grammar are then used to create a tree structure to order the syntactic nodes. The sentence is then generated from the tree structure. The generation grammar is a simplified (context free) version of a corresponding full (context sensitive) analysis grammar. In the generation grammar, conditions on each rule are ignored except those directly related to the semantic representation. The statistical goodness measure values, which are calculated through an analysis training phase in which a corpus of example sentences is processed using the full analysis grammar, are used to guide the generation choice to prefer substructures most commonly found in a particular syntactic / semantic context during analysis.

The invention relates to a maximum entropy based Vietnamese cross ambiguity elimination method and belongs to the technical field of natural language processing. The method comprises the steps of firstly performing disambiguation modeling on Vietnamese cross ambiguity field corpora in a formed Vietnamese cross ambiguity field library to obtain a Vietnamese maximum entropy cross ambiguity elimination model; and randomly selecting test corpora from the Vietnamese cross ambiguity field corpora and performing disambiguation through the established Vietnamese maximum entropy cross ambiguity elimination model to obtain a disambiguated parameter sequence. The method effectively eliminates the ambiguities of Vietnamese cross ambiguity words and provides powerful support for work such as lexical analysis, syntactic analysis, semantic analysis, information extraction, information retrieval, machine translation and the like; at present, no related Vietnamese cross ambiguity elimination reports are discovered; and the method achieves a very good effect.

The present invention provides a keyword extraction method, which includes: performing a word segmentation operation on all the analysis sentences of the extracted text to obtain word units of the analysis sentences; acquiring word features of the word units, sentence features of the word units in the corresponding analysis sentences, and the text features of the word unit in the extracted text; based on the machine learning model established by the machine learning algorithm, using the word feature, sentence feature and text feature of the word unit in each analysis sentence, keyword analysis is carried out for each analysis sentence Fetch operation. The present invention also provides a keyword extraction device. The keyword extraction method and the keyword extraction device of the present invention use the word features, sentence features and text features of the word unit to establish a machine learning model, thereby performing keyword extraction for each analysis sentence operation, thereby improving the accuracy of keyword extraction.

The invention discloses a method and device for sentence analysis, which relates to the technical field of language processing, and its main purpose is to solve the problem that in the existing sentence analysis process, the results of semantic analysis are easily interfered by non-keywords, thus leading to accurate sentence analysis Sexual susceptibility issues, improve the accuracy of sentence analysis results. The main technical scheme of the present invention is: obtain basic vocabulary from the sentence to be analyzed; Carry out feature extraction to described basic vocabulary and the sentence to be analyzed respectively, obtain the word feature corresponding to each basic vocabulary and the sentence feature of the sentence to be analyzed; According to the Describe the word features of each basic vocabulary and the sentence features of the sentence to be analyzed, determine the non-key words in the sentence to be analyzed; remove the non-key words from the sentence to be analyzed, so as to eliminate non-key words The sentence to be analyzed after the vocabulary is analyzed. The present invention is used in the process of analyzing sentences.

The embodiment of the present invention discloses a sentence analysis method, device and terminal equipment, wherein the method includes: if the sentence to be analyzed is obtained, using the sentence classification model to classify the sentence to be analyzed, and obtain the sentence to be analyzed belong to at least one classification category; use the entity word recognition model to identify the sentence to be analyzed, and extract at least one entity word from the sentence to be analyzed; according to the determined entity word and the determined classification category , to obtain category statistics for each entity word. By adopting the embodiment of the present invention, the classification category to which multiple substantive words under a certain sentence belong can be determined more accurately and quickly.

The embodiment of the present invention discloses a method, device, and storage medium for automatically generating text summaries based on deep learning, wherein the method includes the following steps: constructing a Chinese corpus; preprocessing the corpus text in the corpus to extract the keyword table in the corpus text; Analyze the sentence feature vectors between the sentences in the corpus text and the sentence itself, and construct the sentence vectorized feature model according to the sentence feature vector; use the sentence vectorized feature model to train the text to be processed and build a model to generate the corresponding text summary . By adopting the present invention, the omission of valuable content can be avoided under the premise of ensuring the accuracy of the abstract generated.

The present invention discloses an implicit feature recognition method based on a word vector model. The method comprises the following steps: obtaining a training corpus, preprocessing the training corpus and then constructing a corresponding emotion word dictionary and an attribute word dictionary; for the preprocessed training corpus, using the word vector model to form a total dictionary, and solving the word vector of each word in the total dictionary to form a corresponding word vector matrix, wherein each row of the word vector matrix corresponds to a word vector of one word in the total dictionary; according to the word vector matrix, setting parameter matrices of the input layer to the mapping layer and the mapping layer to the output layer in the word vector model to obtain a trained word vector model; and using the trained vector model to carry out implicit feature recognition on each implicit feature clause in the to-be-analyzed corpus. According to the method disclosed by the present invention, starting from understanding the sentence semantics, the word vectors are used to represent the semantic information of the words, and the word vector model is used to recognize the attribute words of the implicit feature clauses, so that the recognition accuracy is improved.

The application relates to a construction method and device of a field knowledge library, computer equipment and a storage medium. The method includes: acquiring field core words in a current to-be-constructed field; acquiring corresponding to-be-processed text according to the field core words; splitting the to-be-processed text to obtain corresponding to-be-analyzed sentences; dividing the to-be-analyzed sentences to obtain a plurality of to-be-analyzed words; obtaining target center words from the plurality of to-be-analyzed words according to a preset rule; carrying out syntax structure analysis on the to-be-analyzed sentences to obtain target syntax structures corresponding to the to-be-analyzed sentences; and establishing relationships on the target center words, the field core wordsand the target syntax structures, and storing the relationships into the field knowledge library corresponding to the to-be-constructed field. By using the method, accuracy of knowledge extraction can be improved.

The present disclosure relates to a sentiment analysis method, device, computer-readable storage medium, and electronic equipment. The method includes: obtaining a first participle set of a corpus to be analyzed; performing syntactic analysis on the first participle set through a syntactic analysis model, To obtain the relationship between each participle in the first participle set; according to the relationship between each participle and the preset emotional lexicon, determine the emotional word of the corpus to be analyzed and the object of the emotional word; according to the The emotion words and the objects query a three-dimensional emotion dictionary to determine the emotion type of the corpus to be analyzed, wherein the three-dimensional emotion dictionary includes the correspondence among emotion words, objects of the emotion words, and emotion types. Through the above technical solution, it is possible to accurately determine the different emotion types that the same emotion word may represent when corresponding to different objects, effectively avoid the one-sided result of a single judgment based on the emotion word, and effectively improve the accuracy of emotion analysis.