基于视图的XML重写技术的研究综述

支持正则路径表达式的查询技术,被认为是半结构化数据模式下的XML查询研究领域中一种颇具有研究价值的XML查询计算方法.基于视图的查询重写技术充分利用视图中的信息来对查询进行优化,提高查询效率.本文讨论了对于支持正则路径表达式的XML查询如何进行重写的问题以及对不同技术的分析.     

浅谈XML查询语言研究

XML是随Web发展所得到的必然产物。它已成为当前网络应用(包括数字图书馆、网络编程、Web服务等)中事实上的数据表达、交换的标准。XML查询已经有了很好的技术基础,但由于XML数据它自身所特有的特点,以及和传统数据模型的差别,XML查询在理论上和实现上都还存在很多难点。本文主要为实现XML文档查询系统XQuery探讨了XML查询的各种处理对象。     

XML数据流上的关键字查询

XML数据流上的XPath & XQuery查询处理是目前研究者关注的热点问题,但由于XPath & XQuery查询语言相对复杂,在不知道模式信息的前提下,用户很难通过已有的查询接口得到自己感兴趣的数据片断,因此如何在数据流模型上根据XML数据的特点为用户提供最友好的查询接口就成为一个亟待解决的问题.针对这个问题,创新地提出了在XML数据流上做关键字查询的问题,给出了最小相关连通子树(SRCT)的概念用于处理返回的结果,并设计了一种新的基于栈的Lookup算法,可以有效解决在XML数据流上进行关键字查询的问题,最后通过实验从不同角度对Lookup算法的各项性能指标进行了验证.     

CoSQL RX中基于Tag集的XML关系查询

在目前支持关系及XML数据统一管理的数据库管理系统中,由于XML固有的表达复杂结构数据的特点,以及XQueryXPath查询语言越来越复杂等原因,如果没有对XML数据的树结构以及查询语义有准确的了解,对于一般用户而言,要查询到所需要的信息有一定难度.针对该问题,在已有工作的基础上,设计并实现了一种基于XML标记(Tag)子集的XML查询方法,该方法只需要用户使用类SQL提交针对包含XML数据列的关系表(RXTable)中XML数据的查询,就可以将数据中所有满足条件的XML数据返回,同时可基于该查询结果进行进一步的更精确的查询.     

XML数据索引技术

对XML数据建立有效的索引,是左右XML数据处理性能的重要因素.深入地讨论了目前XML索引技术的研究现状,将XML索引技术分为两大类:节点记录类索引(本身还可以分为3个小的类型)和结构摘要类索引.根据XML数据查询处理效率以及XML数据修改对XML索引的要求,讨论了相关XML索引方法的优点和不足,并归结出XML索引后续研究的3个方向:XML结构信息的获取,路径信息的多维处理,数据修改合法性的有效支持,以及涉及能够同时有效满足XML查询和信息获取的索引.     

面向对象的XML查询系统的设计与实现

设计和开发了面向对象的XML数据查询系统原型OOX(object-oriented XML).OOX系统中包括了面向对象XML数据查询系统的一些核心功能,如存储、索引、查询等.其最大的特点是:它是一个可以实现对富含面向对象XML数据进行查询的XML查询系统;支持用继承扩展的XML模式语言DTD的解析,支持用继承扩展的XML查询语言XML-RL;采用了先进的路经仓索引模式以及高效的查询处理技术,可以实现高效的查询处理.     

基于路径仓的面向对象XML查询处理技术

XML正在迅速成为Internet上数据表示和交换的标准，存储与查询XML数据变得日益重要，如何快速、准确地查询面向对象的XML数据成为当前研究的热点，索引技术是提高查询效率的有效方法。该文基于路径仓索引模式，提出了一种面向对象的XML数据的查询处理技术。     

基于关系的XML存储技术

在不考虑硬件环境的情况下，XML数据在RDBMS中的存储技术从很大程度上决定了基于关系的XML数据查询效率。目前基于关系的XML存储方式分为两大类：模型映射方法（model-mapping approach）和结构映射方法（structure-mapping approach）。根据XML数据查询处理效率，文章讨论了相关XML存储方法的优点和不足，并归结出XML存储后续研究的两个方向：路径信息的多雏处理和数据修改的有效支持。     

XML 数据流上Top-K 关键字查询处理

利用关键字可以在模式未知的情况下对XML数据进行查询.在当前的XML数据流上的关键字查询处理中,打分函数往往不能都满足各种用户不同的需求.提出了一种基于skyline的XML数据流上的Top-K关键字查询.对于这种查询,不需要考虑影响结果与查询相关性的复杂因素,只需利用skyline挑选与查询最相关的结果.提出了两种XML数据流上的有效的基于skyline的Top-K关键查询处理算法,包括对单查询和多查询的处理算法.通过扩展实验对两种算法的有效性和可扩展性进行了验证.经过实验验证,所提出的查询处理算法的效率几乎不受关键字个数、查询结果数量、查询数量等参数的影响,运行时间和文档大小大致呈线性关系.     

一种标签劣质XML数据上的twig查询处理的优化

XML数据中的不正确数据、不一致数据、不精确数据等劣质数据给XML.数据上的有效查询处理带来了挑战.专注于研究标签劣质的XML数据上twig查询处理的优化方法,文中分别给出了优化方法的原理、伪代码、正确性证明和复杂度分析,并通过例子加以解释.通过实验验证了优化方法的效率.     

Efficiently Querying Large XML Data Repositories: A Survey

Extensible markup language (XML) is emerging as a de facto standard for information exchange among various applications on the World Wide Web. There has been a growing need for developing high-performance techniques to query large XML data repositories efficiently. One important problem in XML query processing is twig pattern matching, that is, finding in an XML data tree D all matches that satisfy a specified twig (or path) query pattern Q. In this survey, we review, classify, and compare major techniques for twig pattern matching. Specifically, we consider two classes of major XML query processing techniques: the relational approach and the native approach. The relational approach directly utilizes existing relational database systems to store and query XML data, which enables the use of all important techniques that have been developed for relational databases, whereas in the native approach, specialized storage and query processing systems tailored for XML data are developed from scratch to further improve XML query performance. As implied by existing work, XML data querying and management are developing in the direction of integrating the relational approach with the native approach, which could result in higher query processing performance and also significantly reduce system reengineering costs.     

基于DOM的XML数据库的索引技术研究

XML作为一种数据交换的国际标准，已经贯穿于Internet应用的各个领域之中，如何快速准确地存储和查询XML数据的数据库技术是一个重要的研究课题。XML索引技术对XML数据库查询处理起着至关重要的作用，提出了基于DOM的XML数据库的索引技术(路径连接索引、值索引和引用索引)，解决了传统的基于树的遍历的XML数据查询方法性能上的不足，并着重对处理含有谓词和引用关系等较复杂的查询路径的不同处理方法进行了对比和分析，还给出了索引空间利用率、查询性能和索引维护代价3个方面的标准测试结果，表明新的索引技术可以有效地提高查询处理效率。     

A query refinement framework for xml keyword search

Existing work of XML keyword search focus on how to find relevant and meaningful data fragments for a query, assuming each keyword is intended as part of it. However, in XML keyword search, user queries usually contain irrelevant or mismatched terms, typos etc, which may easily lead to empty or meaningless results. In this paper, we introduce the problem of content-aware XML keyword query refinement, where the search engine should judiciously decide whether a user query Q needs to be refined during the processing of Q, and find a list of promising refined query candidates which guarantee to have meaningful matching results over the XML data, without any user interaction or a second try. To achieve this goal, we build a novel content-aware XML keyword query refinement framework consisting of two core parts: (1) we build a query ranking model to evaluate the quality of a refined query RQ, which captures the morphological/semantical similarity between Q and RQ and the dependency of keywords of RQ over the XML data; (2) we integrate the exploration of RQ candidates and the generation of their matching results as a single problem, which is fulfilled within a one-time scan of the related keyword inverted lists optimally. Finally, an extensive empirical study verifies the efficiency and effectiveness of our framework.     

基于XML的数据管理技术

随着Web技术的快速发展,如何有效地存储、索引、查询和显示XML数据已经成为数据库研究领域的一个热点研究问题。本文介绍了XML数据的3种不同存储方法;XML搜索查询的工具和语言;XML数据的访问控制模型;XML最直接的显示方法以及正在实现的真正的XML数据库等。通过这些XML数据管理技术,可以了解到当下XML研究领域的先进技术和方法,指导今后的研究方向和重点。     

Adaptive relaxation for querying heterogeneous XML data sources

Searching XML data with a structured XML query can improve the precision of results compared with a keyword search. However, the structural heterogeneity of the large number of XML data sources makes it difficult to answer the structured query exactly. As such, query relaxation is necessary. Previous work on XML query relaxation poses the problem of unnecessary computation of a big number of unqualified relaxed queries. To address this issue, we propose an adaptive relaxation approach which relaxes a query against different data sources differently based on their conformed schemas. In this paper, we present a set of techniques that supports this approach, which includes schema-aware relaxation rules for relaxing a query adaptively, a weighted model for ranking relaxed queries, and algorithms for adaptive relaxation of a query and top-k query processing. We discuss results from a comprehensive set of experiments that show the effectiveness and the efficiency of our approach.     

SAIL: Structure-aware indexing for effective and progressive top-k keyword search over XML documents

Keyword search in XML documents has recently gained a lot of research attention. Given a keyword query, existing approaches first compute the lowest common ancestors (LCAs) or their variants of XML elements that contain the input keywords, and then identify the subtrees rooted at the LCAs as the answer. In this the paper we study how to use the rich structural relationships embedded in XML documents to facilitate the processing of keyword queries. We develop a novel method, called SAIL, to index such structural relationships for efficient XML keyword search. We propose the concept of minimal-cost trees to answer keyword queries and devise structure-aware indices to maintain the structural relationships for efficiently identifying the minimal-cost trees. For effectively and progressively identifying the top-k answers, we develop techniques using link-based relevance ranking and keyword-pair-based ranking. To reduce the index size, we incorporate a numbering scheme, namely schema-aware dewey code, into our structure-aware indices. Experimental results on real data sets show that our method outperforms state-of-the-art approaches significantly, in both answer quality and search efficiency.     

XML文档流上的一种关键字查询方法研究

本文将当前数据库领域的2个研究热点-XML文档和数据流处理一的最新研究结合起来,提出了XML文档流关键字查询的问题。基于最小连通子树的概念。设计了相应的数据结构和基于栈的查询算法,可以有效解决XML文档流上进行关键字查询的问题。具体方法是把XML数据流表示成3类SAX事件：BEGIN（tag）、END（tag）和TEXT0。对每类事件的处理算法进行了详细,并进行了正确性证明。从理论上分析了算法的复杂度,并在XMark和treebank．xml两个数据集上对所提方法进行了广泛的实验。结果验证了本文工作的有效性。     

Query Intent Disambiguation of Keyword-Based Semantic Entity Search in Dataspaces

Keyword query has attracted much research attention due to its simplicity and wide applications. The inherent ambiguity of keyword query is prone to unsatisfied query results. Moreover some existing techniques on Web query, keyword query in relational databases and XML databases cannot be completely applied to keyword query in dataspaces. So we propose KeymanticES, a novel keyword-based semantic entity search mechanism in dataspaces which combines both keyword query and semantic query features. And we focus on query intent disambiguation problem and propose a novel three-step approach to resolve it. Extensive experimental results show the effectiveness and correctness of our proposed approach.