1) (semi-) structured documents
结构(半结构)化文档
2) semi-structured document
半结构化文档
1.
Large scales of electronic information and knowledge, which are available from the Internet, are hidden in semi-structured documents.
在目前的互联网中,大量电子信息资源以半结构化文档的形式存在,对半结构化文档中的内容信息实现有效的抽取并加以利用,具有良好的应用前景和研究价值。
3) structured document
结构化文档
1.
The main task of a question-answer system is to locate the most matching answer from the underlying structured document collection.
结构化文档由标题、章节、段落等逻辑结构组成。
2.
This paper adopts the method based on co-occurrence analysis to learn the term relationships,applies these relationships to the structured document retrieval,and presents a structured document retrieval model based on Bayesian network,gives the topology,probability estimation and the inference process of this model.
采用共现分析的方法从文档集合中学习得到术语之间的关系,并应用到结构化文档检索中,提出了一个基于贝叶斯网络的结构化文档检索模型,给出了其拓扑结构、概率估计以及推理过程。
3.
As multi-layered Bayesian network for structured documents retrieval is proposed,in which term similarity relationships captured by the means of synonyms from collections are used.
从文档集合中挖掘术语间的同义词关系,引入术语相似度对其进行量化,综合运用文档的文本信息和结构信息,提出一个基于同义词扩展的多层贝叶斯网络检索模型,用于实现结构化文档检索任务。
4) document structure
文档结构
1.
Based on the extensibility of PDF document structure,these objects structural expressions is expressed in tagged PDF.
为了在PDF中描述这些对象,对标签PDF文档结构作了研究,阐述了如何在标签PDF文档中结构化地表示科技文档对象,并用plug-in编程接口做了实现。
2.
On the basis of document structure and page tree,the compressed image data can be exactly positioned and then be extracted in the order of pages.
算法结合PDF文档结构和页面树,按照图像在页面中出现的顺序,对各页面中含有的图像对象进行准确定位,依次提取其中的图像压缩数据,并根据采用压缩算法的不同,对压缩数据进行筛选,最后得到保存为JPEG格式的图像。
3.
Describes the document structure in the OpenOffice.
org的XML元数据读取的意义以及它和文档结构化其他研究的关系。
5) file structure
文档结构
1.
Based on the analysis of the deficiency of the traditional vector space retrieval model, the file structure based vector space retrieval model is presented.
分析了传统向量空间检索模型在网络信息检索中的不足 ,给出了基于文档结构的向量空间检索模型。
6) structured document retrieval
结构化文档检索
1.
This paper adopts the method based on co-occurrence analysis to learn the term relationships,applies these relationships to the structured document retrieval,and presents a structured document retrieval model based on Bayesian network,gives the topology,probability estimation and the inference process of this model.
采用共现分析的方法从文档集合中学习得到术语之间的关系,并应用到结构化文档检索中,提出了一个基于贝叶斯网络的结构化文档检索模型,给出了其拓扑结构、概率估计以及推理过程。
补充资料：一文半文
1.指极少的钱。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条