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Seq2seq model-based structured argument generation method and system

A generation system and structured technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as poor correlation and consistency between sentences and sentence sources, low accuracy, and inability to meet user needs , to achieve the effect of improving relevance and consistency, improving accuracy, and improving reliability

Inactive Publication Date: 2018-03-23
CAPITAL NORMAL UNIVERSITY
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Problems solved by technology

However, the accuracy of text generation in related technologies is not high, and the correlation and consistency between the generated sentences and sentence sources are poor, which cannot meet the needs of users.

Method used

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  • Seq2seq model-based structured argument generation method and system
  • Seq2seq model-based structured argument generation method and system
  • Seq2seq model-based structured argument generation method and system

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Embodiment Construction

[0029] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary and are intended to explain the present invention and should not be construed as limiting the present invention.

[0030] Before introducing the structured argument generation method and system based on the seq2seq model, first briefly describe the way the arguments in the paper are developed.

[0031] Argumentative essay is a very important writing genre, and it is also the most widely used genre. Argumentative essays are also called argumentative essays, which are a style of writing that analyzes things, discusses affairs, expresses opinions, and puts forward claims. A good argumentative essay should reflect a certain law of thinking in it...

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Abstract

The invention discloses a seq2seq model-based structured argument generation method and system. The method comprises the following steps of preprocessing data to establish sentence pairs for an inputof a seq2seq model; receiving an input topic and converting words through vector conversion to obtain word vectors; inputting the word vectors to an encoder of the seq2seq model to perform calculationand encoding to obtain a context vector, and adopting an attention mechanism for the context vector; and through the encoder of the seq2seq model, decoding the context vector processed through the attention mechanism through a decoder of the seq2seq model to generate main and sub arguments related to the input topic, and according to the main and sub arguments, obtaining multiple sub-sub arguments in the main and sub arguments. According to the method, randomly initialized word vectors of an original model can be replaced with pre-trained word vectors; and the attention mechanism is added tothe seq2seq model, so that the model reliability is improved and the model accuracy and consistency are effectively ensured.

Description

technical field [0001] The invention relates to the technical field of text generation, in particular to a method and system for generating structured arguments based on a seq2seq model. Background technique [0002] At present, automatic writing is an important application of text generation. The generation of sub-points of argumentative essays is a very important link in automatic writing. How to make the sub-points have a strong correlation and fit with the theme is the text generation technology. One of the puzzles. [0003] In related technologies, text generation is based on statistical machine translation. The basic idea is to construct a statistical translation model by performing statistical analysis on a large amount of parallel corpus, and then use this model for translation. For example, Microsoft Couplet designed a multi-stage statistical machine translation method, in which the SMT (Statistical Machine Translation, statistical machine translation) system gener...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/28
CPCG06F40/44G06F40/55G06F40/58
Inventor 宋巍刘彤刘丽珍
Owner CAPITAL NORMAL UNIVERSITY
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