面向Web的XML文档数据管理及分类检索技术研究
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摘要
随着计算机和互联网技术的发展,网络已经成为资源数量最多、种类最全、规模最大的综合信息库,这些信息大致可分为两类:结构化数据和非结构化数据,据统计,非结构化数据占有整个信息量的80%以上,在信息传递过程中,80%的时间是用来获取信息,因此,如何从Web网上科学高效地获取信息即是本文研究的意义所在。
XML数据库技术和Web搜索引擎技术的发展为提高Web信息检索特别是非结构化数据的检索效率带来了希望。因为XML数据库技术提供了信息存储和管理的技术保障,而搜索引擎技术为Web信息检索构建了操作平台。基于此,本文针对XML文档数据管理技术及面向Web的分类检索技术做了深入细致的研究。本文主要研究内容和创新性工作如下:
首先,综述和分析了纯XML数据库和使能XML数据库的管理技术及索引机制,在分析各种数据模型特点基础上,研究讨论了以关系数据库作为存储源、扩展XQuery作为数据模型的优势,通过对XQuery数据模型的扩展,提出了基于Schema模式约束的XML数据存储和索引结构SBXI,从用户逻辑层面定义了XML文档更新语言XUL,并应用Kweelt查询系统和JAVA技术实现了文档更新的关键技术。
然后,解决了XML网页分类的关键技术-信息检索模型问题。由于传统的向量空间模型不能适用于XML文档结构相似度比较,提出了基于TreeMiner算法的频繁结构向量模型,构建了文档特征矩阵的表示方法和相似度函数;并对该模型拓展,进一步提出频繁结构层次向量模型,不仅挖掘XML文档的结构信息,同时抽取表征文档内容的关键词信息,提高了相似度量的准确率。通过对频繁结构挖掘算法TreeMiner进行改进,使其更适合大文档集合的频繁结构挖掘,实验证明基于频繁模式的检索模型具有很好的网页分类效果。
最后,提出了分类检索与全文检索结合的二次检索策略,从系统设计角度构架了以频繁结构层次向量模型作为信息检索模型、SBXI作为索引结构的基于主题分类的Web文献全文检索搜索引擎的系统结构,并讨论了其主要构件的功能和工作流程。
With the development of computer and Internet technology, the network has become the largest integrated information base, whose resources have the largest number and most types. This information can be divided into two categories: structured data and unstructured data. According to statistics, unstructured data possess more than 80% in the entire amount of information, in the process of information transmission, 80% of the time is used to obtain information. So, how to obtain information legitimately and efficiently from the Web on-line is the significance of this paper.
XML database technology and Web search engine technology scant hope for improving efficiency of Web information retrieval especially the unstructured data retrieval. Because that XML database provides technical support for information storage and management, and the search engine builds a platform for Web information retrieval. For this reason, this article does an in-depth and meticulous research for XML data management techniques and classification of Web search technology. The main research and new ideas of this paper are presented as follows:
Firstly, this article reviewed and analysized native XML database and XML-enabled database management and indexing mechanism. On the base of summing up the various characteristics of the data model, it analysized the advantages of the adoption of relational database to store information as data source and extended XQuery as data model, and then put forward XML data storage and index structure SBXI based on Schema constraint by extending XQuery model. At meantime, defined XML document update language XUL from the user level, and realized the key technology of XML document updating using Kweelt Query System and Java programming.
Secondly, resolved the key technology of XML pages classification -information retrieval model problems. As the traditional vector space model can not be applied to XML documents similarity comparison, this paper built Frequent Structure Vector Model based on algorithm TreeMiner, expression of document characteristics matrix and document similarity function. Then, extended this model, put forward Frequent Structure Hierarchy Vector Model further, and improved the similarity measurement precision, not only miner structure information, but also extract keywords information. In order to make it more suitable for mining frequent structures from large collection of documents, we improved the algorithm TreeMiner, the experiments had proved that the retrieval model based on frequent structure is very good for classification XML pages.
At last, provided the thinking of search twice which combined classification retrieval to full-text retrieval. From the point of system design, we build the framework of Web documents full-text search retrieval engine based on theme classification, which adopts FSHVM as information retrieval model and uses SBXI as index structure, and discussed the main components of the functions and work processes.
XML数据库技术和Web搜索引擎技术的发展为提高Web信息检索特别是非结构化数据的检索效率带来了希望。因为XML数据库技术提供了信息存储和管理的技术保障,而搜索引擎技术为Web信息检索构建了操作平台。基于此,本文针对XML文档数据管理技术及面向Web的分类检索技术做了深入细致的研究。本文主要研究内容和创新性工作如下:
首先,综述和分析了纯XML数据库和使能XML数据库的管理技术及索引机制,在分析各种数据模型特点基础上,研究讨论了以关系数据库作为存储源、扩展XQuery作为数据模型的优势,通过对XQuery数据模型的扩展,提出了基于Schema模式约束的XML数据存储和索引结构SBXI,从用户逻辑层面定义了XML文档更新语言XUL,并应用Kweelt查询系统和JAVA技术实现了文档更新的关键技术。
然后,解决了XML网页分类的关键技术-信息检索模型问题。由于传统的向量空间模型不能适用于XML文档结构相似度比较,提出了基于TreeMiner算法的频繁结构向量模型,构建了文档特征矩阵的表示方法和相似度函数;并对该模型拓展,进一步提出频繁结构层次向量模型,不仅挖掘XML文档的结构信息,同时抽取表征文档内容的关键词信息,提高了相似度量的准确率。通过对频繁结构挖掘算法TreeMiner进行改进,使其更适合大文档集合的频繁结构挖掘,实验证明基于频繁模式的检索模型具有很好的网页分类效果。
最后,提出了分类检索与全文检索结合的二次检索策略,从系统设计角度构架了以频繁结构层次向量模型作为信息检索模型、SBXI作为索引结构的基于主题分类的Web文献全文检索搜索引擎的系统结构,并讨论了其主要构件的功能和工作流程。
With the development of computer and Internet technology, the network has become the largest integrated information base, whose resources have the largest number and most types. This information can be divided into two categories: structured data and unstructured data. According to statistics, unstructured data possess more than 80% in the entire amount of information, in the process of information transmission, 80% of the time is used to obtain information. So, how to obtain information legitimately and efficiently from the Web on-line is the significance of this paper.
XML database technology and Web search engine technology scant hope for improving efficiency of Web information retrieval especially the unstructured data retrieval. Because that XML database provides technical support for information storage and management, and the search engine builds a platform for Web information retrieval. For this reason, this article does an in-depth and meticulous research for XML data management techniques and classification of Web search technology. The main research and new ideas of this paper are presented as follows:
Firstly, this article reviewed and analysized native XML database and XML-enabled database management and indexing mechanism. On the base of summing up the various characteristics of the data model, it analysized the advantages of the adoption of relational database to store information as data source and extended XQuery as data model, and then put forward XML data storage and index structure SBXI based on Schema constraint by extending XQuery model. At meantime, defined XML document update language XUL from the user level, and realized the key technology of XML document updating using Kweelt Query System and Java programming.
Secondly, resolved the key technology of XML pages classification -information retrieval model problems. As the traditional vector space model can not be applied to XML documents similarity comparison, this paper built Frequent Structure Vector Model based on algorithm TreeMiner, expression of document characteristics matrix and document similarity function. Then, extended this model, put forward Frequent Structure Hierarchy Vector Model further, and improved the similarity measurement precision, not only miner structure information, but also extract keywords information. In order to make it more suitable for mining frequent structures from large collection of documents, we improved the algorithm TreeMiner, the experiments had proved that the retrieval model based on frequent structure is very good for classification XML pages.
At last, provided the thinking of search twice which combined classification retrieval to full-text retrieval. From the point of system design, we build the framework of Web documents full-text search retrieval engine based on theme classification, which adopts FSHVM as information retrieval model and uses SBXI as index structure, and discussed the main components of the functions and work processes.
引文
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