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JAVA实现文本聚类，用到TF/IDF权重
- JAVA实现文本聚类，用到TF/IDF权重，用余弦夹角计算文本相似度，用k-means进行数据聚类等数学和统计 知识。,JAVA realization of text clustering, using TF/IDF weight, calculated using cosine angle between the text of similarity, using k-means clustering for data such as mathematical and statistical
java-cluster.zip
- 用java语言实现文本聚类，包括聚类前的数据预处理：分词、降维、建立向量空间模型等,Implementation using java language text clustering, including clustering of the data pre-processing before: segmentation, dimensionality reduction, set up, such as Vector Space Model
MyTest
- 利用wvtool实现文本分类的实例程序,自己写的，功能简单-Text Classification using wvtool instances of programs to achieve their own writing, feature a simple
lingpipe-3.6.0
- 一个自然语言处理的Java开源工具包。LingPipe目前已有很丰富的功能，包括主题分类（Top Classification）、命名实体识别（Named Entity Recognition）、词性标注（Part-of Speech Tagging）、句题检测（Sentence Detection）、查询拼写检查（Query Spell Checking）、兴趣短语检测（Interseting Phrase Detection）、聚类（Clustering）、字符语言建模（Character
Clustering
- 用于文本的聚类，里面包含两个java文件，需放在同一个包内-For text clustering, which contains two java files, need to be placed within the same package
textcluster
- java文本聚类程序代码文件，实现文本聚类功能，分词。-text clustering java code files to achieve text clustering features, sub-word.
src_2
- an another k means clustering fot clustering the text data
mallet-2.0.6
- 关于自然语言处理、机器学习的一个开源软件。-MALLET is an integrated collection of Java code useful for statistical natural language processing, document classification, clustering, information extraction, and other machine learning applications to text.
ClassText
- Several Clustering and classification methods for text documents
MessageClassify
- 通过Kmeans算法实现的文本分类程序，用java写的。-A text clustering program written in java.
Fuzzy-C-Means
- fuzzy c means to perform clustering in java with text documents
TextClustering
- 文本聚类算法包含 tfidf的实现 k-means算法的实现-Text clustering algorithm contains tfidf implementation of the k-means algorithm to achieve
java_kmeans
- java实现kmeans算法，可以处理任意维度的向量。并将聚类结果写入文本。-The kmeans algorithm java, and can handle any dimension vector. And write text clustering results.
textcluster
- Text Clustering, Kmeans Cluster Stop word Handler TermVector TFIDFMeasure Tokeniser
text_example
- text matching and clustering code in java
textcluster
- 基于KMeans的文本聚类算法，支持文本输入，简单易懂-KMeans clustering algorithm based on text, support for text input, easy to understand
textcluster
- 实现文本聚类,初级使用者可以作为参考进行文本聚类知识的辅助学习-The realization of text clustering, primary users can be used as reference for text clustering knowledge assisted learning
Large-scale-text-clustering-master
- java 实现文本聚类 java 实现文本聚类 -the code of text clustering the code of text clustering the code of text clustering
Kmeans-master
- 本程序使用java代码实现一个文本聚类操作，采用的方法是kmens-a simple code of text clustering using kmeans
Kmeans
- 算法思想：提取文档的TF/IDF权重，然后用余弦定理计算两个多维向量的距离来计算两篇文档的相似度，用标准的k-means算法就可以实现文本聚类。源码为java实现(Algorithm idea: extract the TF/IDF weight of the document, then calculate the distance between two multidimensional vectors by cosine theorem, calculate the similarity