Shale gas entity recognition method based on improved neural network
An entity recognition and neural network technology, applied in the fields of shale gas and natural language processing, can solve the problems of inconsistent entity labels and cluttered data structure, and achieve the effect of ensuring high efficiency and accuracy
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[0017] The present invention is a shale gas entity identification method based on an improved neural network. The specific process is as follows: figure 1 shown, is characterized in that, comprises the following steps:
[0018] 1) Preprocess the raw data of shale gas manual annotation, and map the words one by one into a dense vector sequence with contextual semantics;
[0019] 2) Upload the dense vector sequence obtained in step 1) to the convolutional neural network, and obtain the filtered semantics by constraining the filter size in the convolutional neural network and filtering the influence of the local context in the sentence on the recognition of shale gas entities feature;
[0020] 3) uploading the semantic features obtained in step 2) to the bidirectional long-term and short-term memory network, capturing the hidden state of the mark according to the semantic feature context sequence information, and obtaining the global semantic features of the shale gas;
[0021]...
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