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Study on Hot Topics Identification and Key Issues in on-Line News about Emergency Events

机译:关于紧急事件的热门话题识别与关键问题的研究

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Concerning the system of hot topics detection about the emergency events, an overall technical framework is established to implement the system. Description and solution strategy about the key issues in the four components of the system are provided. In terms of the content and structure features of the news reports as well as the distribution feature of the report sources, the text clipping method and the modified model of feature weighting calculation are proposed based on the VSM text representation model and the TF-IDF formula. The news reports about the earthquake emergency event are evaluated for this model as the data sources. Experiment results indicate that the information such as the headline, the lead and relevant feature parameters by clipping the main body of the news report can be considered as the sample set of the hot topics to be identified. Furthermore, compared with the classical model, the modified feature items weighting calculation model is more efficient in execution and more adaptive in terms of the text representation capability.
机译:关于关于紧急事件的热门话题系统的系统,建立了整体技术框架来实现系统。提供了关于系统四个组件中的关键问题的描述和解决方案策略。就新闻报告的内容和结构特征以及报告源的分发特征而言,基于VSM文本表示模型和TF-IDF公​​式提出了文本剪切方法和特征加权计算的修改模型。作为数据源的此模型评估了关于地震紧急事件的新闻报告。实验结果表明,通过剪切新闻报告的主体的标题,铅和相关特征参数等信息可以被视为要识别的热门话题的样本集。此外,与经典模型相比,修改的特征项目加权计算模型在执行和文本表示能力方面的执行和更自适应更有效。

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