An implicit inter-sentence relationship analysis method based on multi-task bi-directional long-short time memory network

Abstract

The invention provides an implicit inter-sentence relationship analysis method based on a multi-task bi-directional long-short time memory network. The method comprises the following steps: obtaininga Chinese text-level semantic relationship corpus, comprising implicit inter-sentence relationship statements and explicit inter-sentence relationship statements; obtaining a Chinese text-level semantic relationship corpus. Using the method of multi-task learning, the input sequence of the model is obtained by using implicit inter-sentence relation recognition task as the main task and explicit inter-sentence relation recognition task as the auxiliary task. Enter both primary and secondary tasks into Bi-LSTM recurrent neural network, through learning the implicit relationship between sentencesrecognition model; The implicit inter-sentence relation recognition model adopts a fusion word embedding method and introduces a priori knowledge so as to make full use of text features and obtain abetter recognition result. The present invention fully utilizes the semantic connection between the implicit sentence-to-sentence relation sentence and the explicit sentence-to-sentence relation sentence, and solves the problem that the implicit sentence-to-sentence relation sentence does not have good characteristics, which leads to bad implicit sentence-to-sentence relation recognition effect.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an implicit inter-sentence relationship analysis method based on a multi-task bidirectional long-short-term memory network. Background technique [0002] Sentence is an important research level besides words, words and phrases in natural language processing. Discourse Rela-tion Recognition is an indispensable part of sentence-level research. The main task of discourse inter-sentence relationship recognition is to study the logical relationship between two consecutive arguments in a text (for example: comparative relationship, extended relationship, parallel relationship and causal relationship, etc.). This task is a fundamental research problem in natural language understanding. Correctly judging the logical relationship between text sentences means being able to effectively understand the semantic relationship of the text. [0003] The difficulty of identifying the implicit...

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Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide an implicit inter-sentence relationship analysis algorithm based on a multi-task bidirectional long-short-term memory network to solve the problem that the recognition of implicit inter-sentence relationship is a low accuracy rate of inter-sentence relationship identification

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