FLORIN - A System to Support (Near) Real-Time Applications on User Generated Content on Daily News

نویسندگان

  • Qingyuan Liu
  • Eduard Constantin Dragut
  • Arjun Mukherjee
  • Weiyi Meng
چکیده

In this paper, we propose a system, FLORIN, which provides support for near real-time applications on user generated content on daily news. FLORIN continuously crawls news outlets for articles and user comments accompanying them. It attaches the articles and comments to daily event stories. It identifies the opinionated content in user comments and performs named entity recognition on news articles. All these pieces of information are organized hierarchically and exportable to other applications. Multiple applications can be built on this data. We have implemented a sentiment analysis system that runs on top of it.

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عنوان ژورنال:
  • PVLDB

دوره 8  شماره 

صفحات  -

تاریخ انتشار 2015