Topic analysis method and device and storage medium

Abstract

The invention discloses a topic analysis method, which comprises the steps of obtaining to-be-processed text corpora, and obtaining a word segmentation result and a corresponding part-of-speech corresponding to each to-be-processed text corpus; obtaining a filtered text corpus; analyzing the word segmentation result and the corresponding part-of-speech of each filtered text corpus through a dependency syntax to obtain a dependency relationship between syntax components of segmented words and the segmented words and a dependency pair corresponding to each text corpus; obtaining a topic corresponding to each text corpus according to the combined sentence pattern structure and the dependency pair; obtaining similar topics, and sorting the similar topics according to the number of the similartopics. The invention also discloses a topic analysis device and a storage medium, syntactic analysis is used on the basis of word segmentation to analyze a dependency relationship between a grammatical structure and a word segmentation result in a text statement, and a smooth and accurate topic is extracted according to a plurality of preset common Chinese combined sentence pattern structures, sothat topics can be analyzed from massive texts.

Description

technical field [0001] The present invention relates to the field of topic analysis and processing, in particular to a topic analysis method, device and storage medium. Background technique [0002] With the rapid development of information technology, the Internet has become the main channel for people to obtain and distribute information. Due to the large amount of network information, wide sources, and fast dissemination speed, it is becoming more and more troublesome for ordinary netizens to quickly and accurately find the network information they want. Therefore, how to quickly, accurately and comprehensively analyze and extract the hot topics concerned by netizens from the massive network information has become a very popular research direction at present. [0003] At present, texts are still the main way of expressing online topics, and the technical means of discovering topics from texts at this stage is still limited to the lexical level, that is, relying on keywor...

AI Technical Summary

Problems solved by technology

That is, the topic and the article are not in a one-to-one relationship, and the clustering algorithm believes that a text has only one topic, so it cannot fully summarize the core content of the entire text

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