Event trigger word extraction method based on document level attention mechanism

An event-triggered and attention technology, applied in special data processing applications, instruments, biological neural network models, etc., can solve the problems of event type aggregation, lack of specificity, and inability to obtain text-level information in a targeted manner.

Active Publication Date: 2018-11-16
DALIAN UNIV OF TECH
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Problems solved by technology

However, the events involved in a document are often related, and there is a phenomenon of event types clustering in the document
There is a way to use the topic model to introduce chapter-level features, but for the can

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  • Event trigger word extraction method based on document level attention mechanism
  • Event trigger word extraction method based on document level attention mechanism
  • Event trigger word extraction method based on document level attention mechanism

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Embodiment Construction

[0047] The present invention will be further described below in conjunction with accompanying drawing.

[0048] Such as figure 1 As shown, an event-triggered word extraction method based on document-level attention mechanism includes the following steps:

[0049] Step 1. Training corpus preprocessing. The training corpus used is selected from MLEE or Multi-Level EventExtraction, and the training corpus is marked with BIO tags. The training corpus provides three files for each document, namely the original text file and entity labeling file and event annotation files, in which event trigger words and events composed of event trigger words and entities are respectively marked in the event annotation files. and trigger words are marked, specifically including the following sub-steps:

[0050] (a) Segment the words and symbols in the text and save them line by line as the first column of the training corpus;

[0051] (b) The entity type and trigger word type corresponding to ea...

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Abstract

The invention relates to an event trigger word extraction method, in particular to an event trigger word extraction method based on a document level attention mechanism, comprising the following steps: (1) preprocessing training corpus; (2) performing word vector training by using PubMed database corpus; (3) constructing a distributed representation way of a sample; (4) constructing a characteristic representation way based on BiLSTM-Attention; (5) adopting CRF learning, and acquiring an optimal sequence labeling result of the current document sequence; and (6) extracting event trigger words.The method provided by the invention has the advantages that firstly a BIO tag labeling way is adopted, and recognition including multi-word trigger word recognition is realized; secondly a corresponding simple word and characteristic distributed representation way is constructed for a trigger word recognition task; and thirdly, a BiLSTM-Attention model is proposed, a distributed representation structure specific to the currently input document level information is realized by introducing an Attention mechanism, and trigger word recognition effect is improved.

Description

technical field [0001] The present invention relates to a method for extracting event-triggered words, and more specifically, relates to a method for extracting event-triggered words based on a document-level attention mechanism. Background technique [0002] As a form of information extraction, event extraction aims to extract structured event information from natural language text. An event usually consists of a trigger word or phrase (Trigger) and several event elements (Argument). Trigger words are usually verbs or nouns with the nature of verbs, which are used to indicate the type of event. Then around the trigger words, the participating elements of the event, the event elements, are identified. Trigger word recognition is a key step in event extraction, and the recognition performance directly determines the accuracy of event extraction. [0003] In the past, the recognition of trigger words was regarded as a multi-classification task, and the candidate words in th...

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Application Information

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IPC IPC(8): G06F17/30G06N3/04
CPCG06N3/045
Inventor 王健王安然林鸿飞
Owner DALIAN UNIV OF TECH
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