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An Incremental Algorithm of Text Clustering Based on Semantic Sequences

机译:基于语义序列的文本聚类增量算法

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摘要

This paper proposed an incremental textcluster-ing algorithm based on semantic sequence. Using similarity relation of semantic sequences and calculating the cover of similarity semantic sequences set, the candidate cluster with minimum entropy overlapvalue was selected as a result cluster every time in this algorithm. The comparison of experimental results shows that the precision of the algorithm is higher than other algorithms under same conditions and this is obvious especially on long documentsset.
机译:提出了一种基于语义序列的增量文本聚类算法。通过使用语义序列的相似关系并计算相似语义序列集的覆盖率,该算法每次都选择具有最小熵重叠值的候选聚类作为结果聚类。实验结果的比较表明,在相同条件下,该算法的精度要高于其他算法,这一点在长文档集上尤为明显。

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