Unsupervised semantic clustering of Twitter hashtags

被引：5
|
作者：
Vicient, Carlos [1 ]
Moreno, Antonio [1 ]
机构：
[1] Univ Rovira & Virgili, Dept Math & Comp Sci, E-43007 Tarragona, Catalonia, Spain
来源：
21ST EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2014) | 2014年 / 263卷
关键词：
D O I：
10.3233/978-1-61499-419-0-1119
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Social micro-blogging networks such as Twitter provide an enormous amount of information, and their automated and unsupervised analysis constitutes an exciting research challenge in Artificial Intelligence. This work presents a novel methodology, based on a semantic clustering of the set of hashtags, which permits to obtain automatically the topics associated to a given set of tweets. A case study on the field of Oncology shows how the main topics of interest are successfully discovered.
引用
收藏
页码：1119 / 1120
页数：2
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