This study explored the locus of category clustering process by means of the manipulation levels of attention at the encoding or retrieval period in short term memory.
本研究通过对短时记忆的编码或提取阶段进行注意分散来探讨范畴群集的定位问题。
Using clustering analysis method on the classification of Chinas urban air quality levels, gather into the city air quality in most similar category, analysis of causes, concluded.
运用聚类分析方法对我国城市空气质量等级进行分类，把空气质量状况最相似的城市聚成一类，分析原因、得出结论。
Clustering group the absence category labels data by similarity degree, there are high similarity inner group and low similarity between groups.
聚类是通过相似度对没有类别标号的数据集中数据进行分组，使得组内对象相似度高而组间相似度低。
The clustering was for two purpose: clustering the over segmented parts and determining the category of the new clustering parts.
聚类的目的有两个，一是为了将过分割的小块聚合，二是要辨别各个重新组合成的块的类别。
First we make a loose classification with k-means clustering algorithm to fix a category of interest.
先用 -均值聚类算法作粗糙划分，确定感兴趣类。
A new clustering algorithm named SCT is raised, which makes system be more suitable to the category data in data source of ontology.
为了适应本体数据源大量的分类数据，提出了一种新的聚类算法sct，实现数据库元组的自动聚类以及概念层次结构的生成。
Using clustering analysis method on the classification of China's urban air quality levels, gather into the city air quality in most similar category, analysis of causes, concluded.
运用聚类分析方法对我国城市空气质量等级进行分类，把空气质量状况最相似的城市聚成一类，分析原因、得出结论。
Using clustering analysis method on the classification of China's urban air quality levels, gather into the city air quality in most similar category, analysis of causes, concluded.
运用聚类分析方法对我国城市空气质量等级进行分类，把空气质量状况最相似的城市聚成一类，分析原因、得出结论。
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