聚类检索

论述了基于内容的图像检索技术（CBIR）的新进展，提出了引入相关反馈机制、多种特征组合检索、图像聚类检索等三种改进其性能的方法，并通过实例论证了这些方法的有效性。

This paper mainly discusses the development of the CBIR in the digital library and puts forward three methods to improve the performance of CBIR system and demonstrates the effectiveness of relevant feedback technique , composite retrieval and the clustering technique by example .

基于小波多尺度特征的图像聚类检索

Wavelet Multi & scale Features Clustering Based Image Retrieval

描述了一种图像数据库中基于小波多尺度特征内容的聚类检索方法。

A wavelet multi & scale features clustering based Image retrieval approach is proposed in this paper .

聚类检索述评

Review of Clustering Retrieval

在处理单个的、小数据量的查询检索上，基于度量聚类检索具有一定的优势。

The retrieval based on clustered metric have certain advantages when dealing with single query and query of small amount data .

聚类检索通过聚类产生相似数据的分类，并以此为基础进行数据查询，从而提高数据检索的效率。

Cluster retrieval method can produce classification of similar data through clustering , and data searching is processed based on this . It can effectively enhance the data retrieval efficiency .

实验表明，该模型有效的提高了领域文本检索准确度。（4）以云南旅游领域作为受限领域，设计并实现了云南旅游领域问答系统的文本聚类检索原型。

Experiments indicate that the proposed model increased the text accuracy substantially . ( 4 ) We designed and realized the text clustering retrieval prototype system based on Yunnan tourism .

机械3维CAD模型的聚类和检索

Clustering & retrieval of mechanical 3D CAD models

然后对于颜色特征，改进了在HSV颜色空间基于颜色统计量化和聚类的检索算法与其相似性度量方法。

With the introduction of HSV color space and the specialties of medical image , a feature extraction algorithm based on color statistical clustering and the corresponding similarity measure are discussed .

基于语义相似度的案例相似度计算对提高案例聚类和检索准确度具有很高的价值。

The similarity computation based on semantic similarity case has a high value to raise the case clustering and retrieval accuracy .

文本聚类是信息检索（Informationretrieval：IR）和数据挖掘（DATAMINING：DM）等领域的一个重要研究方向。

Document clustering is one of most important research topic in information retrieval ( IR ) and data mining ( DM ) .

一种P2P系统节点聚类及信息检索算法

A node clustering and information retrieval algorithm on P2P system

一种基于语言概念空间聚类的信息检索方法

An Information Retrieval Method Based on Language Concept Space Using Clustering Method

基于查询词聚类的信息检索系统排序模型

An Information Retrieval System Ranking Model Based on Query Clustering

一种新的基于模糊聚类的镜头检索方法

A New Approach for Content-based Shot Retrieval by Fuzzy Classification

基于支持向量机的两阶段模糊聚类在视频检索中的应用

Video Retrieval Based on Two-phrase Fuzzy Fusion with SVM

基于聚类的图像检索

Image Retrieval Based on Clustering Algorithm

基于灰关联规则和连通分支的聚类算法情报检索系统用户相关性判断的灰色聚类决策

Clustering Algorithm Based on Gray Association Rule and Connected Component Grey Clustering Decision Method for Information End-User Relevance Judgments

借鉴聚类在文本检索中的应用，聚类可以被用来解决网络视频的组织和分类问题。

With the successful use of clustering in text retrieval , clustering can be employed to solve the organizing and categorizing issue of web videos .

相比一般文本聚类问题，检索结果聚类针对搜索引擎返回文本信息不全的特点，且有着计算速度快、类别描述准确等需求。

Compared with traditional text clustering tasks , search result clustering faces extra challenges such as incomplete texts , real time computing and accurate cluster labeling .

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。

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 .

基于最近邻聚类的INTERNET信息检索系统

Information Retrieval System for Internet based on Nearest Neighbor-clustering

基于聚类的XML文档检索反馈机制研究

Research on a Feedback Mechanism for XML Document Retrieval Based on Clustering

灰关联度聚类算法在图像检索中的应用

Application of gray association degree clustering algorithm in image retrieval

基于学习聚类的图像语义检索算法

An Image Semantic Retrieval Algorithm Based on Learning Clustering

基于模糊聚类分析的数据检索的应用

Application of Data Search Based on Fuzzy Cluster Analysis

基于快速聚类索引的图像检索系统

Image retrieval system based on fast clustering indexing

一种新的颜色聚类算法及其图象检索

A New Color Cluster Algorithm and Image Retrieval

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。

An information retrieval model based on language concept space and a clustering method which serves the IR model is propsed .

实验表明该方法提取的特征维数少，聚类时间短，检索速度快，具有良好的检索性能。

Experiments indicate the proposed method has superb retrieval function with less feature dimension , shorter clustering time and quicker retrieval speed .