Common approaches to unsupervised learning include k-Means, hierarchical clustering, and self-organizing maps.

无监管学习的常见方法包括k - Means、分层集群和自组织地图。

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This paper presents a new method of text clustering by using the latent semantic index (LSI) and self-organizing neural network (SNN).

根据隐含语义索引（LSI）理论和动态自组织映射神经网络理论，提出了一种文本聚类的新方法。

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In this paper, the basic principle of the clustering algorithm based on self-organizing feature map network is discussed, and pointed out its defects.

本文讨论了基于自组织特征映射网络聚类算法的基本原理，并指出了算法的缺陷。

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