System and method of discovering social group having unspecified behavior senses in multi-dimensional space

Abstract

The invention relates to a system and a method of discovering a social group having unspecified behavior senses in a multi-dimensional space, and belongs to the data mining and knowledge discovery field. Whether users having similar behavior relation can be discovered according to similarity of tweet publishing geographic positions and similarity of unspecified behavior senses expressed by the tweet entries based on user social network twitter behavior tracks. According to the experiment, the accuracy of the method provided by the invention of discovering the groups having the similar behaviors is better than the conventional determination method, and therefore the high actual application value can be provided. When the system and the method provided by the invention can be popularized to the greatest extent, the industry innovation can be facilitated, the trans-boundary integration can be prompted, and the great benefits to the social livelihood can be provided, and then the national economic and social innovative development can be prompted.

Description

technical field [0001] The invention belongs to the fields of data mining and knowledge discovery, and specifically relates to a social group discovery system and method for uncertain behavior semantics in a multi-scale space. Background technique [0002] With the rapid popularization of social network applications, more and more users are integrated into social networks. Typical applications include domestic Sina Weibo, foreign Twitter (Twitter), etc. These social applications allow users to share their latest news And ideas are posted to mobile phones or websites in the form of text messages, and if users wish, they can also post Weibo-tweeting physical location information. Weibo-Tweet content is short, but it contains certain semantics, which can be used to deduce user behavior to a certain extent; and allowing the disclosure of physical location information can facilitate tracking the latest updates of users. If the above two aspects can be effectively By using it, we...

AI Technical Summary

Problems solved by technology

[0003] Regrettably, so far, in the research of behavioral semantics, almost all research results believe that behavioral semantics is deterministic, but in fact, behavioral semantics itself often has a certain degree of uncertainty. When the "entry set (asetofterms)" corresponding to the text expresses the "activity" semantics implied by the behavior, there is an uncertain semantic mapping relationship between the "entry" and the "activity". For example, an "entry" It can belong to multiple "activities", and a "activity" can contain multiple entries. It is the uncertainty of this semantic mapping that affects the accuracy of user groups with similar behaviors to a certain extent. However, the current problem However, it has not been able to attract the attention of relevant personnel

On the other hand, when using social data such as Weibo and Twitter to serve various applications, the influence of different geospatial scales on the clustering of social groups is not fully considered.

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