A Text Automatic Summarization Method Based on Fusion Semantic Clustering

Abstract

The invention discloses an automatic text summarization method based on fusion semantic clustering. The method comprises the steps of text preprocessing, wherein preprocessing is conducted on originaldocuments, and word frequency information of keywords in the text is counted; weight calculation, wherein local weights are combined, and global weights and introduced relevant weights are used for determining the contribution degree of the keywords in sentences; semantic analysis, wherein a text matrix is subjected to singular value decomposition to obtain a semantic analysis model to calculatea semantic vector of each sentence; clustering, wherein K sentence clusters are obtained through a clustering algorithm in a semantic space on the basis of the calculated sentence semantic vectors; sentence selection, wherein the sentence weights is calculated in each sentence cluster, the first n sentences are selected to compose an abstract according to ranking, and the redundancy is removed. The method is simple and practical, a characteristic representation is provided for the text, the semantic connection of the context is integrated, a co-occurrence relationship between the sentences andwords is more fully displayed, and the generated abstract can better in line with the theme of the text.

Description

technical field [0001] The invention relates to the technical field of natural language processing, in particular to an automatic text summarization method based on fusion semantic clustering. Background technique [0002] With the development of computer technology and the Internet, great changes have taken place in the way information is disseminated. The Internet has become an important channel for people to obtain resources. But on the other hand, the content of document data on the Internet shows an exponential growth trend, which makes it very necessary to effectively solve the contradiction between information overload and people's fast reading. Automatic text summarization technology provides the possibility for this realization. [0003] Automatic text summarization technology uses a series of text processing technologies to analyze and process lengthy documents through computers, extracts the main ideas of documents, and generates a concise and general summary to...

AI Technical Summary

Problems solved by technology

However, such a method stays literally, does not take advantage of the semantic relationship of the context, and the generated summary lacks relevance

At present, the research on generative summarization mainly focuses on the introduction of deep learning and even reinforcement learning methods. However, due to the current immaturity of related technologies, the generated summaries have grammatical errors, poor readability and coherence, and cannot satisfy users. need

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