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218 results about "Dependency tree" patented technology

A dependence tree is used to apply a tree dependence to approximate probability distributions. A dependence tree indicates the dependence of pixels on other pixels. For example in the figure above shows that for a pixel x k, which pixels are dependent on the others.

Specific target emotion classification method based on attention coding and graph convolution network

The invention provides a specific target emotion classification method based on attention coding and a graph convolution network, and the method comprises the steps: obtaining a context and a hidden state vector corresponding to a specific target through a preset bidirectional recurrent neural network model, and carrying out the multi-head self-attention coding of the context and the hidden statevector; extracting a syntax vector in a syntax dependency tree corresponding to the context by combining a point-by-point convolution graph convolutional neural network, and performing multi-head self-attention coding on the syntax vector; then, multi-head interaction attention is used for carrying out interaction fusion on syntactic information codes, context semantic information codes, syntacticinformation codes and specific target semantic information codes; and splicing the fused result with the context semantic information code to obtain a final feature representation, and obtaining an emotion classification result of the specific target based on the feature representation. Compared with the prior art, the relation between the context and the syntax information and the relation between the specific target and the syntax information are fully considered, and the accuracy of sentiment classification is improved.
Owner:NANJING SILICON INTELLIGENCE TECH CO LTD

Relation extraction method and system based on attention cycle gated graph convolutional network

The invention relates to a relation extraction method and system based on an attention cycle gated graph convolutional network, and the method comprises the steps of carrying out the semantic dependency analysis of a statement, enabling word embedding to be connected with a position feature, and obtaining a final word embedding representation; constructing a BLSTM network layer, and extracting a word context feature vector; applying an attention mechanism to the dependency tree to obtain a soft adjacency matrix of a fully connected graph with weight information; transmitting the word context feature vector and the soft adjacency matrix into a gated graph convolutional network, and extracting a high-order semantic dependence feature to obtain vector representation of a statement; and extracting vector representations of the two marked entities, splicing the extracted vector representations of the two marked entities with the vector representation of the statement, transmitting the spliced vector representation of the statement into a full connection layer of the gated graph convolutional network, calculating the probability of each relationship type and predicting the relationship type, and finally obtaining the relationship type of the statement. According to the invention, key information loss is avoided, and the relationship extraction performance is improved.
Owner:JIANGNAN UNIV

Man-machine interaction question-answering method and system based on complex intention intelligent identification

The invention discloses a man-machine interaction question-answering method and system based on complex intention intelligent recognition, and the method comprises the steps: obtaining an original question sentence of a user, carrying out the sentence segmentation and part-of-speech tagging, and obtaining the part-of-speech information of each component word of the question sentence; performing dependency syntax analysis on the question sentence to obtain a dependency syntax tree; carrying out industry entity identification to obtain industry entities and the number, and extracting a core dependency tree to simplify questions; carrying out industry question relation classification on the questions, carrying out Chinese multi-intention question rewriting, and then carrying out knowledge retrieval on the questions; and selecting and generating answers for knowledge retrieval results, and returning the answers to the user. According to the method and system, multi-intention complex questions can be effectively simplified in any industrial scene, the intention of the user can be accurately understood, the industrial knowledge can be more naturally fed back to the user, the user can more accurately and quickly obtain the required industrial knowledge, the user experience is improved, and the method and system are particularly suitable for man-machine interaction intelligent questions and answers in the medical industry.
Owner:HUNAN UNIV

Method for constructing Vietnamese dependency tree bank on basis of Chinese-Vietnamese vocabulary alignment corpora

The present invention relates to a method for constructing a Vietnamese dependency tree bank on the basis of Chinese-Vietnamese vocabulary alignment corpora and belongs to the technical field of natural language processing. According to the present invention, firstly, a Chinese-Vietnamese vocabulary alignment sentence pair library is constructed; then a Chinese dependency tree corpus is constructed; and according to the constructed Chinese-Vietnamese vocabulary alignment sentence pair library and Chinese dependency tree corpus, a Vietnamese dependency tree corpus is constructed. The Vietnamese dependency tree bank constructed by the method can provide powerful support for upper layer applications of syntactic analysis, machine translation, information acquisition and the like; a bilingual parallel dependency tree corpus is constructed; according to the method for constructing a dependency tree, which is disclosed by the present invention, the process of manually collecting and labeling the Vietnamese dependency tree bank is simplified and labor and time of constructing the tree bank are saved; and compared with a method adopting a machine to carry out learning, the method for constructing a dependency tree, which is disclosed by the present invention, is obviously improved in accuracy.
Owner:KUNMING UNIV OF SCI & TECH

Aspect-level text sentiment classification method and system

The invention discloses an aspect-level text sentiment classification method and system, and the method comprises the steps: extracting the long-distance dependence features of a sentence text according to the obtained local feature vectors of the sentence text, and obtaining the context feature representation of the sentence text; constructing a syntactic dependency relationship among words in the sentence text according to the context feature representation of the sentence text to obtain aspect-level feature representation of the sentence text; and constructing a dependency tree-based graphattention neural network, and obtaining aspect-level emotion categories of the text according to aspect-level feature representation of the sentence text. The method comprises the steps of extractinglocal feature information in a sentence by adopting a convolutional neural network, learning pooled features of the convolutional neural network by utilizing a bidirectional long-short-term memory network, obtaining context information of the sentence, constructing a dependency tree-based graph attention network model, and modeling a sentence dependency relationship by utilizing syntactic information of a dependency tree, thereby improving the performance of sentiment classification.
Owner:SHANDONG NORMAL UNIV

Method for processing unknown words in Chinese-language dependency tree banks

The invention belongs to the field of processing for natural languages of computational linguistics, and discloses a method for processing unknown words in Chinese-language dependency tree banks. The method includes steps of A, searching all synonyms of the unknown words by the aid of synonym forests; B, computing character pattern similarity degrees among the unknown words and all the synonyms of the unknown words according to character pattern features of Chinese characters; C, extracting mapped words and information quantities of word classes of the mapped words when the character pattern similarity degrees among the unknown words and the multiple synonyms are high, and improving character pattern similarity degree computation models; D, extracting the words with the maximum character pattern similarity degrees as the optimal mapped words of the unknown words and using the extracted words as explanation for the unknown words in the tree banks. The method has the advantages that unit pairs (word classes, word classes) in dependency syntactic analysis can be recovered to unit pairs (word classes, words) or unit pairs (words, word classes) on the premise that the scales of the tree banks are no longer expanded, accordingly, the information granularity can be refined, the problem of data sparseness can be solved, and the dependency syntactic analysis performance can be improved.
Owner:BEIJING INFORMATION SCI & TECH UNIV
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