An Automatic Identification Method of Controversial Focus Based on Hierarchical Attention Neural Network Model
A neural network model and automatic recognition technology, applied in biological neural network models, neural learning methods, unstructured text data retrieval, etc., can solve problems such as unfavorable large-scale expansion, time-consuming and laborious construction process, and achieve good scalability. , the effect of reducing manual work and reducing the burden on users
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[0082] Below in conjunction with the method of the present invention describe in detail the concrete steps that this embodiment implements, as follows:
[0083] In this embodiment, the method of the present invention is applied to court judgment documents in the field of commercial housing sales disputes, and the focus of disputes in the documents is automatically identified.
[0084] 1) Use regular expressions to process a total of about 336,000 judgment documents, and extract the court's summary and expression of the disputed focus of the case. Among them, there are more than 15,000 documents containing expressions of the focus of disputes. From these 15,000 documents, a total of 6,418 non-repetitive sentences expressing the focus of disputes can be obtained. First, the TF-IDF algorithm is used to vectorize the text. First, preprocess the text by cutting words and removing stop words, and then build a word bag space. Read all the documents into the program, and follow the...
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