基于XML数据的FP-growth算法挖掘研究

XML是跨平台的数据表示、交换技术,由于其本身在自描述性、开放性等方面的优势,在短短的时间内迅速成为行业标准。大量XML数据的涌现给数据挖掘提出了新的挑战。传统关联规则挖掘是基于关系数据库的,即把XML数据文档映射成关系数据库来完成。给出一个使用FP-growth算法直接从XML文档挖掘关联规则的类接口,并且在J2EE平台下用Java语言实现。     

基于XQUERY和XSLT的不规则XML文档的关联规则挖掘

目前,XQUERY语言实现的Apriori算法只能挖掘结构规整的XML数据,而无法对复杂不规则的XML数据进行挖掘.针对这个问题,改进Apriori算法,引入SDST的概念,使用XSL和XSLT将结构不规整的XML文档转换为SDST,使SDST作为Apriori算法的应用接口,从而实现对复杂不规则XML数据的关联规则挖掘.     

基于树元组的XML函数依赖研究

与关系数据库一样,XML文档可能由于函数依赖而产生数据冗余或操作异常,在关系数据库中对于函数依赖的理论体系的研究已经比较完善,但对XML函数依赖的研究才刚刚起步.结合XML文档类型定义DTD进行探讨,提出基于树元组的XML函数依赖的概念,并结合Armstrong公理系统推导出函数依赖的推理规则集.     

XML文档到关系数据库的转换研究

XML作为网络数据交换的标准技术,广泛应用于计算机软件.目前存储数据的主流手段是关系数据库,因此XML文档与关系数据库之间必须进行转换.通过分析XML文档的层次结构,建立了XML文档树模型,并给出结点定义.依据XML的BNF规则给出了元素与属性的正规表达式和相对应的状态转换图,设计了识别元素和属性的词法分析程序用于解析XML文档.提出了XML文档树到关系数据库存储的转换思想和算法,并结合实例给出转换后的关系表.     

利用关系数据库存储XML文档方法研究

人们对XML的关注源自Web数据挖掘技术对数据源的结构化需求。这里介绍了三种将XML文档存入关系数据库的编码方法。这些编码方法能捕捉到足够的信息来重建有序的XML文档，即从有序的XML文档到关系的映射是无损失的，并展望了它在Web数据挖掘中的应用前景。     

基于ADO.NET实现XML文档与关系数据库转换的方法

由于各个公司的系统存在异构性,如何让各个公司的数据实现交换和共享成为了一个问题,因此出现了用XML作为中间转换载体来实现关系数据库中数据在网络上的共享.如何避免XML文档与关系数据库转换中存在的问题,本文讨论了基于ADO.NET来实现XML文档与关系数据库的转换.     

一种基于RDBMS的XML数据的存储方法

XML作为一种数据交换的标准在互联网上推出,使得XML数据和数据库的相互交换成为必要:一是因为WEB中大量的多样化数据需要进行有效的存储和管理;二是因为在现有的数据库中存储有大量的数据并且需要将这些数据转换为XML发布到WEB中。论文提出了一个基于关系数据库的数据转换框架,基于数据的完整性讨论XML数据存储策略。建立一个XML通用数据模型,把文档树分解成多个节点,根据一定的映射规则存储到关系表中,从而不用考虑文档的模式信息(DTD、XMLSchema)。最后通过一个具体的文档实例来说明这种策略的有效性。     

一种基于分层框架的XML发布方法

因特网的不断发展使得XML成为Web上数据交换和表示的标准格式,但是大量的商业数据仍然存储在关系数据库中。因此必须将关系数据发布成XML文档进行传输。提出了一种基于分层框架结构的关系数据库向XML的映射方法,并在分层结构中定义了一种XML模式图作为XML的概念模型。得到的XML文档能够很好地反映关系数据库的语义和各种约束并且没有引入数据冗余。初步实验结果表明方法具有较高的效率和较好的准确性。     

XML的数据处理技术在ERP中的使用

由于XML自身的特点,它非常适合作为异构数据源之间数据转换的中介。本系统集成中采用XML作为数据转搀的中介．实现了不同数据库之间的数据转换,并且实现了XML文档与关系数据库之间数据相互转换的构件。提高了ERP系统的可扩展性、灵活性和可维护性。该文分析了ERP系统中数据转换的基本需求,结合面向对象的方法和构件技术．设计并实现了基于XML的通用数据转换系统。本文总结了在实施ERP系统的实践中所使用的技术,提出了用标准XML模式作为交换单据的数据标识：详细描述了关系模式与XML模式之间映射的转换脚本：讨论了XML文档与关系数据库之间相互转换的数据转换构件的设计和实现接口：并基于DOM解析器,详细介绍了数据库转换构件中的数据转换的算法。在具体的使用过程中,只要对每种单据都生成一份简单直观的转换脚本,并调用数据转换构件的接口,就可以非常容易地提取（或存储）带有层次关系的XML文档。     

基于XML的实时数据一致性描述与查询处理

实时数据查询技术在工业企业信息平台中具有广泛的用途，XML数据标准能够实现各子系统数据的统一描述。该文用成熟的关系数据库查询机制处理符合DTD的XML文档，提出了一整套数据模型、转换规则、算法描述，可以将XML文档转换为关系元组，从而达到用XML实现基于关系数据库的实时数据一致性描述和查询处理的目的。     

Tractable XML data exchange via relations

We consider data exchange for XML documents: given source and target schemas, a mapping between them, and a document conforming to the source schema, construct a target document and answer target queries in a way that is consistent with the source information. The problem has primarily been studied in the relational context, in which data-exchange systems have also been built. Since many XML documents are stored in relations, it is natural to consider using a relational system for XML data exchange. However, there is a complexity mismatch between query answering in relational and in XML data exchange. This indicates that to make the use of relational systems possible, restrictions have to be imposed on XML schemas and mappings, as well as on XML shredding schemes. We isolate a set of five requirements that must be fulfilled in order to have a faithful representation of the XML data-exchange problem by a relational translation. We then demonstrate that these requirements naturally suggest the in-lining technique for data-exchange tasks. Our key contribution is to provide shredding algorithms for schemas, documents, mappings and queries, and demonstrate that they enable us to correctly perform XML data-exchange tasks using a relational system.     

基于关系数据库的XML数据管理

Currently,there are a great of research topics that focus on storing and querying XML data in an RDBMS,and publishing relational data as XML documents ,and querying XML views of relational data. An overview of XML data management based on RDBMS is given in this paper. Some existing technologies of storing and querying XML data in relational databases ,publishing relational data as XML documents ,and querying XML views of relational dataare sufficiently surveyed,their advantages ,disadvantages ,and causes are analyzed.     

An efficient and scalable algorithm for clustering XML documents by structure

With the standardization of XML as an information exchange language over the Internet, a huge amount of information is formatted in XML documents. In order to analyze this information efficiently, decomposing the XML documents and storing them in relational tables is a popular practice. However, query processing becomes expensive since, in many cases, an excessive number of joins is required to recover information from the fragmented data. If a collection consists of documents with different structures (for example, they come from different DTDs), mining clusters in the documents could alleviate the fragmentation problem. We propose a hierarchical algorithm (S-GRACE) for clustering XML documents based on structural information in the data. The notion of structure graph (s-graph) is proposed, supporting a computationally efficient distance metric defined between documents and sets of documents. This simple metric yields our new clustering algorithm which is efficient and effective, compared to other approaches based on tree-edit distance. Experiments on real data show that our algorithm can discover clusters not easily identified by manual inspection.     

从DTD映射到关系模式:一种保持数据依赖的映射方法

XML正迅速成为互联网上数据表示和交换的标准．用关系数据库存储XML数据是XML存储策略之一．为了将XML数据存储到关系数据库中，人们研究了从DTD到关系模式的映射方法．提出了一种保持数据依赖的映射方法PDD．与已有的Shared—Inlining方法相比，PDD方法充分考虑了DTD蕴涵的数据依赖关系，保证了XML文档的完整性．通过对泛关系进行模式分解，得到的关系模式保持函数依赖，并且满足2NF．可以证明，这种方法是有效的．     

基于．net的关系型数据库数据转XML方法研究

XML以其可扩展性、结构性以及平台无关性的优点迅速使其成为Internet数据交换的标准,基于XML的数据集成成为现在研究的热点。通过研究关系型数据库数据转XML技术,设计并实现了基于．net的关系型数据库数据转XML方法,该方法通过调用DataSet类的WriteXml方法可以将关系型数据库表转化为XML文档,具有很大的应用价值。     

XML structural delta mining: Issues and challenges

Recently, there is an increasing research efforts in XML data mining. These research efforts largely assumed that XML documents are static. However, in reality, the documents are rarely static. In this paper, we propose a novel research problem called XML structural delta mining. The objective of XML structural delta mining is to discover knowledge by analyzing structural evolution pattern (also called structural delta) of history of XML documents. Unlike existing approaches, XML structural delta mining focuses on the dynamic and temporal features of XML data. Furthermore, the data source for this novel mining technique is a sequence of historical versions of an XML document rather than a set of snapshot XML documents. Such mining technique can be useful in many applications such as change detection for very large XML documents, efficient XML indexing, XML search engine, etc. Our aim in this paper is not to provide a specific solution to a particular mining problem. Rather, we present the vision of the mining framework and present the issues and challenges for three types of XML structural delta mining: identifying various interesting structures, discovering association rules from structural deltas, and structural change pattern-based classification.     

基于区间编码方案分裂大型XML文档到关系存储

将一个XML文档分裂存储到关系数据库中，通常的方法是利用DOM对该XML文档进行解析，并利用DOM接口提供的XML文档树信息来实现分裂。但是，DOM在解析一个大型XML文档时效率特别低，甚至是无法胜任。文中对转换XML文档到关系数据库中进行存储和查询的策略以及区间编码方案进行了综述；基于区间编码方案探讨了如何分裂一个大型XML文档到关系存储的基本原理，并给出了相应的算法。实验结果表明，该方法是通用的、高效的。     

Mapping DTDs to relational schemas with semantic constraints

XML is becoming a prevalent format and standard for data exchange in many applications. With the increase of XML data, there is an urgent need to research some efficient methods to store and manage XML data. As relational databases are the primary choices for this purpose considering their data management power, it is necessary to research the problem of mapping XML schemas to relational schemas. The semantics of XML schemas are crucial to design, query, and store XML documents and functional dependencies are very important representations of semantic information of XML schemas. As DTDs are one of the most frequently used schemas for XML documents in these days, we will use DTDs as schemas of XML documents here. This paper proposes the concept and the formal definition of XML functional dependencies over DTDs. A method to map XML DTDs to relational schemas with constraints such as functional dependencies, domain constraints, choice constraints, reference constraints, and cardinality constraints over DTDs is given, which can preserve the structures of DTDs as well as the semantics implied by the above constraints over DTDs. The concepts and method of mapping DTDs to relational schemas presented in the paper can be extended to the field of XML Schema just with some modifications in related formal definitions.     

XML structural delta mining: Issues and challenges

Recently, there is an increasing research efforts in XML data mining. These research efforts largely assumed that XML documents are static. However, in reality, the documents are rarely static. In this paper, we propose a novel research problem called XML structural delta mining. The objective of XML structural delta mining is to discover knowledge by analyzing structural evolution pattern (also called structural delta) of history of XML documents. Unlike existing approaches, XML structural delta mining focuses on the dynamic and temporal features of XML data. Furthermore, the data source for this novel mining technique is a sequence of historical versions of an XML document rather than a set of snapshot XML documents. Such mining technique can be useful in many applications such as change detection for very large XML documents, efficient XML indexing, XML search engine, etc. Our aim in this paper is not to provide a specific solution to a particular mining problem. Rather, we present the vision of the mining framework and present the issues and challenges for three types of XML structural delta mining: identifying various interesting structures, discovering association rules from structural deltas, and structural change pattern-based classification.