Extraction type document automatic abstracting method based on context semantic perception

Abstract

The invention discloses an extraction type document automatic abstracting method based on context semantic perception. The extraction type document automatic abstracting method mainly solves the problem that a traditional algorithm lacks the recognition degree of sentences in different contexts. The method comprises: firstly, using an LDA topic model for calculating topic probability distributionin a document, and then determining the similarity between each sentence and a topic word; extracting semantic features of sentences by using a CNN model, further calculating the similarity between each sentence and the features, finally adding values of topic similarity and feature similarity of each sentence to obtain a final sentence score, and taking a proper number of sentences as abstracts according to score ranking. According to the method, a topic model and a deep learning model are introduced, a topic abstracting method is determined, sentence meanings in different contexts can be analyzed more accurately, and a calculation reference method is provided for other automatic document abstracting methods.

Description

technical field [0001] The invention belongs to the field of natural language processing, and relates to an extractive document automatic summarization method based on context semantic perception, which applies the LDA topic model and deep learning method to automatic text summarization, and solves the lack of understanding of semantic information in current document automatic summarization The problem. Background technique [0002] With the continuous development of modern Internet technology, the amount of data generated every day is very explosive. How to extract effective information from massive data has become an urgent need. Automatic text summarization is the use of computers to refine a large amount of data content. A technique for producing a concise, concise summary that replaces the content of an entire document. According to different types of algorithms, mainstream technologies are divided into traditional algorithms based on word frequency statistics and algo...

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Problems solved by technology

[0005] The purpose of the present invention is: in order to solve the lack of understanding of the contextual semantic relationship in automatic document summarization, resulting in a single and one-sided summarization result, thereby proposing an extractive document automatic summarization method based on contextual semantic awareness

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