An image annotation method based on mutual information and constrained clustering is proposed.
提出一种基于互信息约束聚类的图像标注算法。
Based on concept space and text clustering technique as well as traditional keyword searching method, it could help users to locate the information they need quickly and precisely.
这种检索方法在文本聚类的基础上，基于概念空间并与传统的关键词检索相结合能够帮助用户快速、准确地定位所需要查找的信息。
According to the characteristics of the related texts, this paper presents a sentence clustering method based on multi-features for getting profile information of the event.
本文利用事件相关文档的特点，提出了基于多特征的句子聚类方法，以期获得事件的各个侧面信息。
The method mines information on overlap between classes, designs the tree structure and overcomes the misclassification of tree-structured SVMs based on the semi-fuzzy kernel clustering algorithm.
该方法基于半模糊核聚类算法挖掘不同类别之间的衔接和离散信息，设计树型支持向量机的树型结构，克服其差错积累问题。
The concepts of high attribute dimensional information system are firstly proposed, and a new dynamic clustering method on the basis of sparse feature difference degree is presented.
针对高属性维稀疏数据聚类问题，提出高属性维稀疏信息系统概念，给出一种新的基于稀疏特征差异度的动态抽象聚类方法。
An information retrieval model based on language concept space and a clustering method which serves the IR model is propsed.
提出了一种以语言概念空间中的概念为聚类对象的信息检索方法以及适合于该方法的聚类算法。
In this paper, a method of information clustering and concept association is shown, it is based on neural network, and it aims at inkling information searching in knowledge discovery.
针对知识发现中的信息模糊查询问题，提出了一种基于神经网络的信息聚类及联想实现方法。
This method breaks through the traditional design ideas, for the usage of information clustering of concept lattice Characteristics. And it also broadens the application of concept lattices.
该方法利用了概念格对信息聚类的特性，突破了传统方法相关度计算方法的设计思路，拓宽了概念格的应用范围。
This paper introduced a new feature selection method, which first used clustering to reduce redundancy among features and then used Information Gain to choose good features.
针对这一问题，提出了一种基于聚类的特征选择方法，先使用聚类的方法对特征间的冗余性进行裁减，然后使用信息增益的方法选取类别区分能力强的特征。
Results HPLC/ELSD and constellation graphical clustering method properly revealed the quality information apparently and accurately.
结果本法直观、准确地表达了产品的质量信息。
Shannon's mutual information and fuzzy entropy clustering based oil analysis method was presented.
应用信息熵及模糊熵聚类算法对油液监测数据间的关联关系进行考察。
Shannon's mutual information and fuzzy entropy clustering based oil analysis method was presented.
应用信息熵及模糊熵聚类算法对油液监测数据间的关联关系进行考察。
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