Method and device for iteratively updating feature lexicon in social network

Abstract

The invention discloses an iteration updating method and device of feature word banks of fields in the SNS (Social Networking Service). The method comprises the following steps: performing iteration updating on a feature word bank of a field according to the text content released by a user group in the field in the SNS, wherein one-time iteration updating process comprises the step of computing the relevancy between the content of each text released by each user in the user group of the field and the field according to the feature word bank of the current field; computing the relevancy between the user and the field according to the relevancy between the content of each text released by the user and the field; confirming users having the relevancy larger than a first relevancy threshold value with the field among the user group of the field, using the text content, released by the confirmed users and having the relevancy larger than a second relevancy threshold value with the field, as the corpus of the field, and extracting feature words of the field from the corpus, so as to obtain the feature word bank of the field. According to the invention, the accuracy of the feature word bank of the field can be improved.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a method and device for iteratively updating a feature lexicon in a social network. Background technique [0002] With the development of Internet technology, sharing, dissemination and acquisition of information through social networks has become one of the main social methods for the majority of network users. For example, through social networks such as Weibo or Twitter (Twitter), users can publish their own latest developments and other content, and can also comment on, bookmark or forward content published by other users. [0003] In practical applications, through the observation and analysis of social networks such as Weibo, it is found that social circles in different fields, large and small, are distributed in social networks. For different domains in the social network, operators usually establish a feature lexicon for each domain to classify a large number of use...

AI Technical Summary

Problems solved by technology

However, because the content of web pages in related fields is edited by web page editors, which is quite different from the colloquial text content in social networks, the feature lexicon constructed based on the corpus crawled by web crawlers is used in In social networks, its accuracy is not high, which in turn will affect the classification of text content in social networks or the accuracy determined by domain experts

[0006] To sum up, the accuracy of the feature lexicon in the field of the existing social network is not high enough

Images