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Editorial: Survey and Experimental Analysis of Event Detection Techniques for Twitter

机译:社论:Twitter事件检测技术的调查和实验分析

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摘要

Twitter's popularity as a source of up-to-date news and information is constantly increasing. In response to this trend, numerous event detection techniques have been proposed to cope with the rate and volume of Twitter data streams. Although most of these works conduct some evaluation of the proposed technique, a comparative study is often omitted. In this paper, we present a survey and experimental analysis of state-of-the-art event detection techniques for Twitter data streams. In order to conduct this study, we define a series of measures to support the quantitative and qualitative comparison. We demonstrate the effectiveness of these measures by applying them to event detection techniques as well as to baseline approaches using real-world Twitter streaming data.
机译:Twitter作为最新新闻和信息来源的受欢迎程度正在不断提高。为了响应这种趋势,已经提出了许多事件检测技术来应对Twitter数据流的速率和数量。尽管这些工作大多数都对所提出的技术进行了一些评估,但经常会省略比较研究。在本文中,我们对Twitter数据流的最新事件检测技术进行了调查和实验分析。为了进行这项研究,我们定义了一系列支持定量和定性比较的措施。我们通过将它们应用于事件检测技术以及使用真实Twitter流数据的基线方法来证明这些措施的有效性。

著录项

  • 来源
    《The Computer journal》 |2017年第3期|329-346|共18页
  • 作者单位

    Department of Computer and Information Science, University of Konstanz, P.O. Box 188, 78457 Konstanz, Germany;

    Department of Computer and Information Science, University of Konstanz, P.O. Box 188, 78457 Konstanz, Germany;

    Department of Computer and Information Science, University of Konstanz, P.O. Box 188, 78457 Konstanz, Germany;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    performance evaluation; event detection; Twitter data streams;

    机译:绩效评估;事件检测;Twitter数据流;

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