A neural network event extraction method fusing an attention mechanism

An event extraction and neural network technology, applied in the field of natural language processing, can solve problems such as inaccurate classification, and achieve the effect of good ability

Inactive Publication Date: 2019-05-03
HANGZHOU DIANZI UNIV
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Problems solved by technology

[0003] Aiming at the problem that polysemous words are used as event-triggering words due to polysemous words in event extraction, the present invention discloses an event extraction method based on a contextual attention mechanism and a two-way GRU network

Method used

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  • A neural network event extraction method fusing an attention mechanism
  • A neural network event extraction method fusing an attention mechanism
  • A neural network event extraction method fusing an attention mechanism

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Embodiment

[0060] Obtain the event text to be extracted, and perform word segmentation processing on the text. After processing, the words are converted into word vectors through the trained word2vec model. Input the trained bidirectional GRU neural network to obtain the extracted event trigger words and corresponding event types.

[0061] Such as figure 1 , use the processed word vector and the corresponding label to input the bidirectional GRU neural network of collaborative context attention, initialize the neural network parameters with the obtained weight, and adjust the neurons through BP backpropagation according to the GRU part and the attention mechanism part. The weights of the two-way GRU neural network with trained synergistic contextual attention are obtained. And use the trained two-way GRU model to process the event text to be extracted. Specific steps include:

[0062] Input the preprocessed training text (word vector and corresponding event annotation) into the bidir...

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Abstract

The invention discloses a neural network event extraction method fusing an attention mechanism. The method comprises the following implementation steps: (1) preprocessing a training sample and a to-be-extracted event text; (2) training a bidirectional GRU network of a collaborative context attention mechanism by using the preprocessed training sample; (3) inputting the to-be-extracted event text into the trained neural network, and outputting the extracted event trigger word and the predicted event type; According to the method, the context attention mechanism is utilized to cooperate with thebidirectional GRU network to analyze the text, so that the polysemy recognition capability in event trigger word recognition is improved, and the method has more accurate event classification capability.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, relates to event extraction and event detection related methods, and is specifically used for extracting events from unstructured text and classifying the events. Background technique [0002] Event extraction is to extract events of interest to users from unstructured information and present them to users in a structured manner. The current main research methods are pattern matching and machine learning. Pattern matching can achieve high performance in specific fields, but poor portability. Compared with pattern matching, machine learning has nothing to do with the domain, does not require too much guidance from domain experts, and has better system portability. With the construction of related corpora and the continuous enrichment of various text resources on the Internet, the acquisition of corpus is no longer the bottleneck that restricts machine learning. At present, m...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06K9/62G06N3/04G06N3/08
Inventor 汤景凡戚铖杰张旻姜明闻涛
Owner HANGZHOU DIANZI UNIV
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