This method uses frequent term set clustering to compress massive data and uses semantic information to improve accuracy .

该算法使用频繁 词集 聚类来压缩数据，并使用语义信息进行分类。

Mid - long term load forecast of power system is affected by various uncertain factors and research shows that clustering method can synthesize numerous relative factors and put them into forecast model .

中 长期电力系统负荷预测受大量不确定因素的影响，研究表明 聚类方法能够将各种影响因素综合引入预测模型。

Novel method of frequent term set s-based text clustering was presented .

提出了基于频繁 特征 项集的文档 聚类方法。

On the basis of an improved semantic affinity based term clustering algorithm a semantic-based clustering approach for concept generation is proposed . Domain concepts are generated through semantic affinity based term clustering while terms are extracted from term sets of heterogeneous knowledge sources .

改进了基于语义相似度的 术语 聚类算法，在此基础上提出了基于语义聚类的概念生成方法，其基本思想是由各知识源的术语集合，通过基于语义相似度的术语聚类，生成领域概念。

Document clustering approach based on term clustering and association rules

一种基于 术语 簇和关联规则的文档聚类方法

Study on term clustering techniques

词 聚类方法研究

As the result of enriching the linguistical rules the coverage of rules is enlarged and the recall is improved . Secondly a single-word term recognition approach based on fuzzy clustering is proposed according to the simple structure and the unambiguous boundary .

丰富语言规则的同时，扩大了规则覆盖面，提高术语抽取的召回率。2.针对单词型 术语结构简单，边界清晰的特征，提出一种基于模糊 聚类的识别算法。

Power System Short Term Load Forecasting Based upon a Combination of Markov Chain and Fuzzy Clustering

基于马尔可夫链和模糊 聚类的电力系统 短期负荷预测

The Duplex Strategy of Term Weighting in Text Clustering

文本 聚类 中 权重计算的对偶性策略

The paper also analyzes the algorithm of statistics-based term extraction normalization term-document matrix construction singular value decomposition and hierarchical agglomerative clustering .

接着，本文讨论了这三个步骤所涉及的算法，包括基于统计模式对文本抽 词、基于奇异值分解 从 词&文档矩阵中提取本体、基于语义 相似度对 本体进行 聚类等。

A Single-Word Term Recognition Approach Based on FCM Clustering Algorithm

基于FCM 聚类算法的单词型 术语识别方法

Finally an information retrieval system based on the LSI is implemented the term transfer relation for the information retrieval initial results are selected and the results by document clustering algorithm are adjusted .

最后本文实现了一个基于潜在语义索引的文本检索系统，对检索的初始结果进行 特征传递关系选择并通过 聚类手段调整检索结果。

An iteration method is proposed to deal with the duplex phenomena found in term weighting and compute out the latent concept . Experimental results show that the latent concept could help to get better clustering results .

利用迭代的方法来处理和利用这种对偶性，获得了文本的隐含概念.实验结果表明，采用概念空间代替原始 词空间来表示文本，能够得到更好的 聚类结果。

A model for short term and super short term forecasting integrating neural network expert system and dynamic clustering is introduced here which involves weather festival and other load forecasting affecting factors .

介绍了一种整合神经网络、专家系统和动态 聚类多种智能方法为一体的短期/超 短期预测模型，综合考虑了气象、节假日等负荷影响因素。

A Study of Term Expressing and Clustering Method of Text Mining

文本挖掘中的 特征表示及 聚类方法

Massive short documents classification method based on frequent term set clustering

基于频繁 词集 聚类的海量短文分类方法

First of all the pairwise constraint sets are found out in feature term set . After that the constraint sets can be expanded by using the K-nearest neighbors set method and clustering according to the partition results of the constraint set .

此方法是通常先找出特征 词库中的成对约束集，再用K最近邻近集的方法对成对约束集进行扩充， 聚类后将每个 簇中的特征 词合并成一个新的属性。