搜索资源列表
2007Z
- 语义平滑文件模式聚类,代表了文本挖掘的前沿技术,和热门方向(英语原版)-semantic document clustering model, the representative of the Text Mining of advanced technology, and popular direction (English original)
LJClusterDemo
- 文本聚类是基于相似性算法的自动聚类技术，自动对大量无类别的文档进行归类，把内容相近的文档归为一类，并自动为该类生成特征主题词。适用于自动生成热点舆论专题、重大新闻事件追踪、情报的可视化分析等诸多应用。 灵玖Lingjoin（www.lingjoin.com）基于核心特征发现技术，突破了传统聚类方法空间消耗大，处理时间长的瓶颈；不仅聚类速度快，而且准确率高，内存消耗小，特别适合于超大规模的语料聚类和短文本的语料聚类。 灵玖文档聚类组件的主要特色在于： 1、速度快：可以处理海量规模
0010
- 基于WEKA平台的文本聚类及实现，以及常用的文本聚类效果评价指标-Text clustering based on WEKA platform and implementation, as well as common text clustering validity
File10
- Web文档聚类系统的设计与实现：数据挖掘；聚类分柝：文本挖掘；预处理；聚类组合；可 视化；欧氏距离-Web Document Clustering Design and Implementation: Data mining Clustering Hierarchical: text mining pretreatment cluster combinations visualization Euclidean distance
Introduction-to-Information-Retrieval
- Introduction to Information Retrieval is the first textbook with a coherent treatment of classical and web information retrieval, including web search and the related areas of text classification and text clustering. Written from a computer sci
InformationRetrieval
- 关于信息检索技术的说明和文本聚类简介，介绍了几种主要文本聚类算法-Introduction to Information Retrieval and Text Clustering
Similarity-Measures-for-Text-Document-Clustering.
- Similarity Measures for Text Document Clustering
ClusteringAnalysis
- java实现的K-Means文本聚类文章，采用英文撰写，需要源码的可以发邮件lixinle@yahoo.cn。-java realize the K-Means Text Clustering articles written in English to the source code can email lixinle@yahoo.cn.
text-clustering
- 文本聚类及主题挖掘相关论文合集，包括了kmeans，层次聚类，ap聚类等等相关方法-Text clustering and topic mining related collection of papers
frequent-term-based-text-clustering
- 一篇很好的基于主题的聚类方法论文，可以用在文本分类等众多领域-frequent term-based text clustering
wenbenleiju
- 基于文本相似度计算的文本聚类算法研究与实现，这是中文信息处理的重要分支。-The text clustering algorithm based on text similarity computing research and implementation, this is an important branch of Chinese information processing.
Text-Clustering-Doc
- Text Document Clustering Document for the MCA and Mtech Students for the final year projects.This Document Clustering is based on several algorithms and full document is presented here.
sigmod14-density-based-clustering
- 社会网络分析中的密度估计方法，发表在sigmod2014上的深度文章，有具体算法和实验评价-Social network analysis density estimation method was published in sigmod2014 good text, be able to estimate the social networks of small groups and core.
cluster
- 提出了一种基于语义内积空间模型的文本 聚类算法. -Text proposed clustering algorithm within the semantic model based on the product space.
文本分析聚类实战
- 文本挖掘是从大量的文本数据中抽取隐含的，求和的，可能有用的信息。 通过文本挖掘实现 ?Associate：关联分析，根据同时出现的频率找出关联规则 ?Cluster：将相似的文档（词条）进行聚类 ?Categorize：将文本划分到预先定义的类别里(Text mining is a kind of information that is extracted from a large number of text data, which may be useful. Implementa