An innovative user-attentive framework for supporting real-time detection and mining of streaming microblog posts

被引：0
|
作者：
A. Cuzzocrea
G. Pilato
机构：
[1] University of Trieste,DIA Department
[2] ICAR-CNR,undefined
来源：
Soft Computing | 2020年 / 24卷
关键词：
Attentive user management systems; Real-time detection of streaming microblog posts; Real-time mining of streaming microblog posts; Opinion mining; Sentiment mining;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we present a modular system capable of catching the attention of a new user, to detect in real-time events and emotions related to them in a stream of microblog posts. The system is capable of making social sensing and exploiting the information arising on the Internet through user-generated contents, and it is equipped with a conversational engine that manages the interaction with the human user. The whole approach can be applied either by a human user or a robot, which remains a future application to be further improved in the context of our proposed system.
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页码：9663 / 9682
页数：19
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