document clustering信息详情
文件聚类；文件分群；文本聚类
document───vt.记录，记载；n.文件，公文；[计]文档；证件
clustering overview───群集概述
clustering ensemble───聚类融合
divisive clustering───分裂聚类
clustering survey───聚类调查
document scan───文档扫描
clustering metric───聚类度量
clustering nodes───群集节点
word document───Word文档
All document clustering methods are based on keywords now.───现有的文献聚类方法都是通过文献关键词来进行的。
This paper presents a method to study interdisciplines by document clustering analysis.───本文提出了一种通过文献数据聚类分析来研究学科交叉的方法。
Document clustering had been employed in information filtering, web page classification and so on.───文本聚类在信息过滤，网页分类中有着很好的应用。但它面临数据量大，特征维度高的难点。
detecting hotspot of discipline; topic clustering; topic extraction; document clustering.───学科热点监测；主题聚类；主题抽取；文本聚类。
It uses the document clustering to find multi-interests of each user and the accuracy of describing user's interests is improved.───利用文档聚类发现用户的多个子兴趣主题，从而提高对用户兴趣偏好描述的准确性。
Document clustering description is a problem of labeling the clustered results of document collection clustering.───标注文本集合聚类后生成的类簇被称为聚类描述问题。
The thesis proposes a new document clustering method that uses a model named Document Index Graph to represent Chinese documents.───本文提出的一种新的文本聚类方法，采用一种称为文档索引图的结构来构建中文文本表示模型。
Needle document clustering results This paper lists several common methods for assessment.───针文档聚类的结果本文列举了几个常见的评估方法。
And then comes the document clustering techniques.───于是，文本聚类技术应运而生。
A multi-level document clustering algorithm was proposed based on association rules, It constructed document feature vector of topic and keyword by using a new method of document feature extraction.
This paper proposed the algorithm for a document clustering based on similarity to overcome the drawbacks of ordinary information search.
To improve document clustering, a document similarity measure based on cosine vector and keywords frequency in documents is proposed, but also with an input ontology.
The thesis proposes a new document clustering method that uses a model named Document Index Graph to represent Chinese documents.
All document clustering methods are based on keywords now.
Experiments show that the automatic parameter setting in document clustering generates more satisfied clustering result and improves the clustering efficiency.
It uses the document clustering to find multi-interests of each user and the accuracy of describing user's interests is improved.
And then comes the document clustering techniques.
Document clustering had been employed in information filtering, web page classification and so on.