Clustering Orders

Clustering Orders
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聚类订单

DOI:
10.1007/978-3-540-39644-4_17
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发表时间:
2003
期刊:
Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)
影响因子:
--
通讯作者:
Jun Fujiki
Jun Fujiki
中科院分区:
--
文献类型:
--
作者:
Toshihiro Kamishima;Jun Fujiki

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我们提出了一种使用聚类技术来划分一组订单的方法。我们将术语“顺序”定义为根据某些属性(例如大小、偏好或价格)排序的对象序列。这些命令对于进行感官调查等很有用。我们提出了一种称为 k-o’means 方法的方法,它是 k-means 方法的修改版本,经过调整以处理订单。我们将我们的方法与传统的聚类方法进行了比较,并分析了其特点。我们还将我们的方法应用于有关人们对寿司(日本食品)类型偏好的问卷调查数据。
We propose a method of using clustering techniques to partition a set of orders. We define the term order as a sequence of objects that are sorted according to some property, such as size, preference, or price. These orders are useful for, say, carrying out a sensory survey. We propose a method called the k-o’means method, which is a modified version of a k-means method, adjusted to handle orders. We compared our method with the traditional clustering methods, and analyzed its characteristics. We also applied our method to a questionnaire survey data on people’s preferences in types of sushi (a Japanese food).
DOI: 10.1023/a:1009769707641
发表时间: 1998-09-01
影响因子: 4.8
作者:
Huang, ZX
通讯作者: Huang, ZX