Atmospheric Environment and Quality of Life Information Extraction from Twitter with the Use of Self-Organizing Maps
作者: M. Riga M. Stocker M. Rönkkö K. Karatzas M. Kolehmainen
刊名: Journal of Environmental Informatics, 2015, Vol.26 (1)
来源数据库: International Society for Environmental Information Science
DOI: 10.3808/jei.201500311
关键词: air qualityclusteringcomputational intelligencek-meanssemantic analysisself-organizing mapstext miningtwitter
原始语种摘要: The emergence of Web 2.0 technologies has changed dramatically not only the way users perceive the Internet and interact on it but also the way they influence a community and act in real life aspects. With the rapid rise in use and popularity of social media, people tend to share opinions and observations for almost any subject or event in their everyday life. Consequently, microblogging websites have become a rich data source for user-generated information. The leading opportunity is to take advantage of the wisdom of the crowd and to benefit from collective intelligence in any applicable domain. Towards this direction, we focus on the problem of mining and extracting knowledge from unstructured textual content, for the atmospheric environment domain and its effect to quality of life. As...
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  • their 他们的
  • information 报告
  • according 按照
  • opportunity 机会
  • social 群居的
  • learning 学识
  • clustering 聚类
  • atmospheric 大气的
  • almost 几乎
  • applying 施加