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An improved Single-Pass clustering algorithm internet-oriented network topic detection

机译:面向互联网的改进的单遍聚类算法面向互联网的网络主题检测

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The Single-Pass clustering algorithm, its two main disadvantages are easily affected by the orders of inputs of text and low precision when we use it to process the network text clustering. Through introducing the concept of seeds of topic, the paper proposed an improved Single-Pass clustering algorithm which inherited the main means of Single-Pass clustering algorithm. The experiment results showed that the improved algorithm could not only improve the speed of clustering, but also decrease the probabilities of miss detection, false detection, and the cost of wrong detection. The improved Single-Pass clustering algorithm that has improved the quality of clustering and topic detection both has high practicability and good reference value to the research of analysis for internet public opinion.
机译:单次通过聚类算法,它的两个主要缺点很容易受到文本输入顺序的影响,并且在我们使用它处理网络文本聚类时精度较低。通过引入主题种子的概念,提出了一种改进的单遍聚类算法,该算法继承了单遍聚类算法的主要手段。实验结果表明,改进后的算法不仅可以提高聚类的速度,而且可以降低漏检,误检的概率和错误检测的成本。改进的单遍聚类算法提高了聚类和主题检测的质量,具有很高的实用性,对互联网舆情分析研究具有很好的参考价值。

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