A popularity evaluation method for network topics

Abstract

The invention provides a hot degree evaluating method for a network topic. The hot degree evaluating method for the network topic comprises the steps that the attribute of the network topic is compared with attributes in a rule, wherein the rule is obtained through training and is used for indicating the corresponding relation between the attribute of the network topic and the hot degree value; the hot degree value of the network topic is obtained according to the comparison result. According to the hot degree evaluating method for the network topic, a value evaluating system is defined, a user can understand the hot degree of the topic conveniently, and comparison of the hot degrees of topics is facilitated; in addition, centralized inconsistency is optimally trained based on the rough set correlation theory, so that the relation between the hot degree values and the attributes is learnt, and a good hot degree evaluating effect is achieved, wherein unlimited attribute values are dispersed within a limited value range, and thus calculation complexity is reduced; in addition, a training set is obtained by combining users with various kinds of background knowledge, in this way, sample data can be more compressive, and the prejudice of individuals is reduced to the maximum extent.

Description

technical field [0001] The present invention relates to the technical field of data mining, and more specifically, to a popularity evaluation method for network topics. Background technique [0002] The Internet has become the most important carrier of information dissemination, and has consolidated its main position in news dissemination by virtue of its freedom and convenience. Massive and various types of data form an extremely rich source of information on the Internet, and Internet news media has been recognized as the "fourth media" after newspapers, radio, and television. People have become accustomed to checking the latest information through the Internet, but the huge amount of news requires netizens to read the news selectively, so the latest and hottest event-related information has become the focus of attention. [0003] After network information data is collected and extracted, semi-structured or structured web page information becomes easy-to-handle structured...

AI Technical Summary

Problems solved by technology

[0005] Although there have been many achievements in the research on topic popularity, most of them lack a unified measurement standard, and the range of popularity values ​​is often uncertain, and users cannot obtain an intuitive understanding of the current degree of attention of events through numerical values; and, for Most of the parameters in the calculation process are obtained through manual designation or scoring, so the calculation results are biased towards subjectivity; in addition, the comparability of heat values ​​between different time periods is weak, and existing methods often use a certain period of time The corpus is used to calculate the topic ranking, so it cannot be used for the description of topic trends

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