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中文摘要：
提出一种新的文本段落聚类策略，该策略采用多特征融合思想尽可能多地挖掘段落内的特征，并采用累积Logistic回归分析方法来拟合这些特征与段落相似度之间的内在关联，使得段落相似度计算的结果更为理想。最后采用层次聚合聚类算法中的complete—link方法对段落集合进行聚类处理：通过网络真实文本进行了段落相似度度量实验和段落聚类实验，实验结果显示了方法的可行性。
英文摘要：
Aiming at the difference between paragraphs clustering and traditional full texts clustering in useable information and clustering size, the paper proposes a new clustering strategy. It uses the idea of multiple features fusion to dig useful features as far as possible and uses the cumulative Logistic regression analysis to fit the internal relation between these features and paragraphs similarity. At last, it uses the complete-link method of hierarchical clustering to process the set of paragraphs. The results of the paragraphs similarity computation experiment and the paragraphs clustering experiment show the feasibility of the method.
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