An Implicit Discourse Relationship Analysis Method Based on Hierarchical Depth Semantics
A technology of relational analysis and discourse, applied in semantic analysis, semantic tool creation, natural language data processing, etc., can solve problems such as overfitting and data sparseness, and inability to effectively use implicit discourse relational argument deep semantic information, etc., to achieve Make up for misjudgment, obtain quickly and accurately, and improve the effect of analysis accuracy
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Embodiment 1
[0040] The present embodiment has specifically described the flow chart of the proposed method of the present invention and the method in the present embodiment, as figure 1 shown.
[0041] From figure 1 It can be seen that the proposed method of the present invention includes four modules: a preprocessing part, corresponding to the corpus preprocessing in step 1; a vector initialization part, corresponding to the multi-level semantic vector initialization in step 2; a feature extraction part, corresponding to step 3 Generating and expanding the useful word pair table, and the hierarchical depth semantic representation of the implicit textual relationship in step 4.1; the classification part, corresponding to the neural network model parameter training in steps 4.2 to 4.3, and the implicit textual relationship category score;
[0042]Among them, the wide arrow indicates the data flow direction of the training corpus, and the narrow arrow indicates the data flow direction of ...
Embodiment 2
[0044] This embodiment specifically describes the classification system architecture of the method proposed in the present invention. figure 2 It is the framework diagram of the implicit discourse relationship classification system proposed by the present invention.
[0045] From figure 2 It can be seen that the implicit discourse relationship classification system of the method proposed in the present invention corresponds to the hierarchical depth semantic representation of the implicit discourse relationship in step 4, the training of neural network model parameters, and the scoring of implicit discourse relationship categories. The input from left to right is the implicit discourse relationship distribution vector, namely the product of the prior probability of the implicit discourse relationship and the transition matrix, the implicit discourse relationship argument pair vector, and the implicit discourse relationship useful word pair vector; multi-level After the sema...
Embodiment 3
[0047] This embodiment specifically describes the process of running the implicit discourse relationship analysis based on hierarchical depth semantics on a PC based on the method proposed in the present invention, specifically corresponding to steps 1 to 4 in the content of the invention;
[0048] This embodiment is based on the English tagged corpus Penn Discourse Treebank (PDTB) and its tagged categories, and the unlabeled corpus Central News Agency of Taiwan, English Service (CNA) and Xinhua News Agency, English Service (XIN), and follows the sequence of steps in the content of the invention : Introduce the corpus preprocessing method, the multi-level semantic vector initialization method, the method of generating useful word pairs and expanding the useful word pairs, and the implicit discourse relationship model training and category scoring methods.
[0049] A) Corpus preprocessing, the implementation steps are as follows:
[0050] 1. According to the statistical results...
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