Aviation fault text abstract generation method and device based on fault causal atlas
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A graph and fault technology, applied in the computer field, can solve problems such as logical confusion, order reversal, and unreasonable chapter structure
Pending Publication Date: 2022-03-22
CHINA AERO POLYTECH ESTAB
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However, this kind of generative summary model only satisfies the fluent grammar, but when it is applied to the aviation failure field text, the chapter structure of the generated content will be unreasonable. For example, in the narrative process, the root cause and secondary cause, The sequence of different types of events in the fault occurrence process is reversed, and problems such as logical confusion will occur
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Embodiment 1
[0054] The method for generating abstracts based on the aviation field of the present invention can be applied in the process of summarizing aviation fault texts in the aviation field. For example, for a paragraph of text related to the aviation field, a short summary of the text can be obtained by summarizing the text.
[0055] As an optional implementation, the process is as follows figure 2 As shown, the above-mentioned methods for generating summaries in the field of aviation include:
[0056] S101: Generate a catalog map through the original fault causal map;
[0057] The expression form of the fault causal graph is a graph, which is a topological structure composed of nodes and edges. Events in the fault causal graph are nodes, and the causal relationship between events is an edge. If there is a causal relationship between events, then There is an edge connecting them. The causal map of faults is mainly used to describe the causal relationship between events. The cau...
Embodiment 2
[0092] An embodiment of the present invention provides an abstract generation device 20, such as image 3 shown, including,
[0093] The first acquisition unit 201 is configured to generate an original fault causal map of the catalog map;
[0094] The first input unit 202 is used to input the fault causal map into the directory map generator based on the agglomerative hierarchical clustering method;
[0095] The second obtaining unit 203 is used to obtain the fault causal map added with the catalog map, and the target text sample in the aviation field;
[0096] The second input unit 204 is used to input the target text sample in the aviation field into the text encoder based on the deep text feature extractor;
[0097] The third obtaining unit 205 is used to obtain the vectorized representation and structural features of the fault cause-effect map and the catalog map;
[0098] The third input unit 206 is used to input the structural features of the fault causal map and the ...
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Abstract
The invention discloses an aviation fault text abstract generation method and device based on a fault causal atlas. The method comprises the following steps: step 1, generating a directory atlas through an original fault causal atlas; 2, obtaining a feature vector of a target text sample; 3, generating text candidate abstracts by using the fault causal atlas model; 4, decoding the text generation model; and 5, generating an aviation fault text abstract. According to the method, firstly, a catalog atlas is obtained for a fault causal atlas which is constructed in advance through an agglomerated hierarchical clustering method, then structural features obtained in advance are introduced in the encoding stage and the decoding stage through the fault causal atlas, and finally the needed aviation fault text abstract is generated. According to the method, information extraction is carried out by utilizing a document chapter structure, fault logic positioning is carried out by applying a fault cause and effect graph, and the problem that an existing generative abstract model cannot meet chapter directory structure constraints is solved.
Description
technical field [0001] The present application relates to the field of computer technology, in particular to a method and device for generating aviation fault text summaries based on fault causal graphs. Background technique [0002] The text summarization model can convert long text paragraphs into condensed summary texts, and preserve all the information in the original text as much as possible. Generative summarization is usually a generative language model that uses large-scale corpus pre-training. Input a piece of text as the beginning and continue to write the text through the auto-regression mechanism. After fine-tuning on the summary data, input the original text as the beginning, and the model will generate Abstract of the original text. However, this kind of generative summary model only satisfies the fluent grammar, but when it is applied to the aviation failure field text, the chapter structure of the generated content will be unreasonable. For example, in the n...
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