A streaming topic evolution tracking method for real-time news content

A topic and news technology, applied in the field of Internet and natural language processing, can solve the problems of inability to make full use of topic differences, inability to measure the relevance of topic mining results before and after, lack of rationality and accuracy, etc.

Active Publication Date: 2021-05-11
SOUTHEAST UNIV
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the traditional LDA method cannot measure the relationship between the results of topic mining before and after, and the OLDA method cannot make full use of the differences between topics and between topics in time when describing the relationship between the results of topic mining before and after. Accuracy is lacking

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  • A streaming topic evolution tracking method for real-time news content
  • A streaming topic evolution tracking method for real-time news content
  • A streaming topic evolution tracking method for real-time news content

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Embodiment Construction

[0045] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0046] A streaming topic evolution tracking method (referred to as the dELDA method) for real-time news content is implemented, and its overall workflow is as follows: figure 1 shown. This method first divides the news content collected in real time from the Internet into batches according to time periods, and uses the LDA method to mine preliminary topic results for each batch of news content; then, performs named entity recognition within this batch of news content, and calculates the topic Ass...

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Abstract

The invention discloses a streaming topic evolution tracking method for real-time news content. First, the news content collected in real time is divided into batches according to time periods, and the LDA method is used to mine preliminary topic results for each batch of news content; This batch of news content internally performs named entity recognition, and calculates the relationship between the topic and the entity, so as to update the entity link relationship in the entity library; then, through the clustering of the internal terms of the topic, the corresponding relationship between the topic-topic clusters is obtained, And store the topic results in the topic library; finally, calculate the heat information of the topic and its internal clusters, and dynamically update the LDA topic mining parameters according to the heat information, for the topic evolution tracking of the next batch of news content. The invention can mine the topic features in the real-time news content and the cluster features of the words in the topic, make full use of the differences between topics and different clusters in the topic, and dynamically update the LDA topic mining parameters.

Description

technical field [0001] The present invention relates to a streaming topic evolution tracking method for real-time news content. The method can conduct time-by-segment, streaming topic mining and evolution tracking of news content collected in real time from the Internet by means of dynamic update of topic mining parameters. , belonging to the field of Internet and natural language processing technology. Background technique [0002] In recent years, with the vigorous development of information technology, the Internet has become the most convenient channel for people to obtain information and understand news. However, while the Internet news information resources are extremely rich, it also brings the huge challenge of "information overload", that is, the continuous emergence of massive news content makes it difficult for users to obtain useful parts from them, which in turn affects the quality of news content. Effective utilization. Personalized recommendation technology ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06F16/36G06F16/9535G06F40/295G06F40/30
CPCG06F40/295G06F40/30
Inventor 杨鹏张成帅李幼平张长江
Owner SOUTHEAST UNIV
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