时序性和波动性直接与话题的热度有关,短时间内某话题出现的相关报道越多,则其热度越高;话题的波动幅度越大,则其热度越高.依据积分理论给出了基于时序性的相关报道密度计算和基于波动性的峰值计算,并采用线性调和的方法将二者融合,给出话题热度计算方法.实验采用TDT4语料作为测试集合,验证了该方法的有效性与合理性.
Temporal and volatility are directly related to the hot degree of topic, namely, the more related stories the topic has in a certain time distance, and the larger fluctuation the topic is, the higher hot degree of this topic. Applying integration theory, methods of computing the density of related stories and the peak value are put forward based on temporal and volatility respectively. Finally, linear meditated method is used to merge them to compute the hot degree of a topic. Experiments are carried out on TDT4 corpus to testify the validity and rationality of our new method.
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