从微文本中提取可操作信息
Extracting actionable information from microtexts
摘要：
像Twitter这样的微博是一个强大的信息来源。这一信息的一部分可以汇总到个别员额以外。其中一些汇总信息涉及可以或应该为电子政务、公共安全或其他层面的公共利益采取行动的事件。此外，大量的这类信息如果汇总起来，可以以一种重要的方式补充现有的信息网络。本文提出了一种半自动的方法来提取可操作的信息，服务于这一目的。首先，我们表明，预测时间的事件是可能的域和跨域的情况。第二，我们提出了一种方法，它有利于相关性的定义分析师的背景和使用这个定义来分析新的数据。最后，我们提出了一种方法，结合基于机器学习的相关信息分类方法与基于规则的信息分类技术来分类微文本。从这个研究项目的第一天起，完全自动化的缩微文本分析就一直是我们的目标。我们在这方面的努力使我们了解了这种自动化可以实现的程度。我们首先开发了一种自动化方法，然后通过在自动化方法的各个步骤中集成人工干预来扩展和改进它。我们的经验证实了以前的工作，指出一个精心设计的人的干预或贡献的设计，实现，或评估的信息系统，无论是提高其性能或使其实现。由于我们的研究和结果引导我们走向它的必要性和价值，我们从以前的研究中受到启发，设计了人类参与，并定制了我们的方法，以受益于人类的投入。
英文摘要：
Microblogs such as Twitter represent a powerful source of information. Part of this information can be aggregated beyond the level of individual posts. Some of this aggregated information is referring to events that could or should be acted upon in the interest of e-governance, public safety, or other levels of public interest. Moreover, a significant amount of this information, if aggregated, could complement existing information networks in a non-trivial way. This dissertation proposes a semi-automatic method for extracting actionable information that serves this purpose. First, we show that predicting time to event is possible for both in-domain and cross-domain scenarios. Second, we suggest a method which facilitates the definition of relevance for an analyst's context and the use of this definition to analyze new data. Finally, we propose a method to integrate the machine learning based relevant information classification method with a rule-based information classification technique to classify microtexts. Fully automatizing microtext analysis has been our goal since the first day of this research project. Our efforts in this direction informed us about the extent this automation can be realized. We mostly first developed an automated approach, then we extended and improved it by integrating human intervention at various steps of the automated approach. Our experience confirms previous work that states that a well-designed human intervention or contribution in design, realization, or evaluation of an information system either improves its performance or enables its realization. As our studies and results directed us toward its necessity and value, we were inspired from previous studies in designing human involvement and customized our approaches to benefit from human input.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
