一种基于XML的半结构数据的ORDB存储方法

由于半结构数据缺乏类型信息,因而半结构数据服务器中数据的存储策略将是一个十分重要的研究课题。因为只有有效的存储,才能导致有效的索引及查询处理等技术。正是因为如此,关于如何对半结构数据进行有效的存储亦是目前研究的热点问题。论文在对现有的三种存储方法进行分析的基础上,提出并实现了一种XML数据的ORDB存储策略。     

A Semantic Cache Framework for Secure XML Queries

Secure XML query answering to protect data privacy and semantic cache to speed up XML query answering are two hot spots in current research areas of XML database systems. While both issues are explored respectively in depth,they have not been studied together,that is,the problem of semantic cache for secure XML query answering has not been addressed yet. In this paper,we present an interesting joint of these two aspects and propose an efficient framework of semantic cache for secure XML query answering,which can improve the performance of XML database systems under secure circumstances. Our framework combines access control,user privilege management over XML data and the state-of-the-art semantic XML query cache techniques,to ensure that data are presented only to authorized users in an efficient way. To the best of our knowledge,the approach we propose here is among the first beneficial efforts in a novel perspective of combining caching and security for XML database to improve system performance. The efficiency of our framework is verified by comprehensive experiments.     

一种基于XML的信息搜索技术

以XML形式组织的数据结构层次清晰,语义明确。本文利用XML技术的这一特点,提出了一种基于XML的信息搜索方法：以用户需求信息的结构为基准,根据拓扑匹配原则,以倒向路径（L-R）的拓扑匹配为出发点,给出了信息搜索时有关用户需求在某一数据源中的匹配度Tmd计算方法。     

基于领域本体和关系模型的XML语义集成方法研究

由于缺乏足够的语义信息,不同模式的XML数据之间很难进行互操作。针对油气井工程中的XML数据集成需求,借助领域全局本体,提出一种模式无关的XML语义集成方法。该方法首先在XML Path路径与领域本体之间进行语义映射,屏蔽其模式差异;然后,按照模型映射方法将XML存储为关系数据;最后通过查询重写将SPARQL转换为SQL语句,实现语义查询。该方法对XML模式进行语义标注,利用关系数据库存储与查询XML数据,能有效处理领域XML数据的语义集成。     

Access Structures for Angular Similarity Queries

Angular similarity measures have been utilized by several database applications to define semantic similarity between various data types such as text documents, time-series, images, and scientific data. Although similarity searches based on Euclidean distance have been extensively studied in the database community, processing of angular similarity searches has been relatively untouched. Problems due to a mismatch in the underlying geometry as well as the high dimensionality of the data make current techniques either inapplicable or their use results in poor performance. This brings up the need for effective indexing methods for angular similarity queries. We first discuss how to efficiently process such queries and propose effective access structures suited to angular similarity measures. In particular, we propose two classes of access structures, namely, angular-sweep and cone-shell, which perform different types of quantization based on the angular orientation of the data objects. We also develop query processing algorithms that utilize these structures as dense indices. The proposed techniques are shown to be scalable with respect to both dimensionality and the size of the data. Our experimental results on real data sets from various applications show two to three orders of magnitude of speedup over the current techniques     

Efficient storage of healthcare data in XML-based smart cards

In this paper we present storage structures for efficiently processing XML path queries on healthcare data stored in smart cards using XML format. In the design of the storage structures that we present, properties of healthcare data and fundamental types of queries on the healthcare data are taken into account as well as the constraints of the smart cards. We compare the space and time efficiency of the proposed storage structures for various types of queries.     

一种新的XML文档的存储平台SDML的实现技术

目前,XML文档数据库(NXD—Native XML DBMS)的设计和存储正受到越来越多的关注,这是由于它可以灵活地表示各种数据,尤其是那些关系模式无法表达的复杂的数据。已经有一些NXD产品出现。而对XML文档的存储的好坏直接影响到它的查询效率,基于此我们自主提出了一种高效的XML文档存储平台SDML。详细讨论了它的存储结构和实现细节。特别提出了如何解决具有大量结构相同元素的存储方法,并给出了在其上进行查询、插入、删除和索引维护等操作的解决方案。给出了这种结构I／O费用代价,并进行了相关的实现,为NXD的存储优化提供一种新的途径。     

XML data update management in XML-enabled database

With the increasing demand for a proper and efficient XML data storage, XML-Enabled Database (XEnDB) has emerged as one of the popular solutions. It claims to combine the pros and limit the cons of the traditional Database Management Systems (DBMS) and Native XML Database (NXD). In this paper, we focus on XML data update management in XEnDB. Our aim is to preserve the conceptual semantic constraints and to avoid inconsistencies in XML data during update operations. In this current era when XML data interchange mostly occurs in a commercial setting, it is highly critical that data exchanged be correct at all times, and hence data integrity in XML data is paramount. To achieve our goal, we firstly classify different constraints in XML documents. Secondly, we transform these constraints into XML Schema with embedded SQL annotations. Thirdly, we propose a generic update methodology that utilizes the proposed schema. We then implement the method in one of the current XEnDB products. Since XEnDB has a Relational Model as the underlying data model, our update method uses the SQL/XML as a standard language. Finally, we also analyze the processing performance.     

集成Web 数据的系统框架与实现方法

基于我们正在研究和开发的项目Panorama，本文提出了一个基于XML和CORBA的Web数据集成系统框架，该框架可以集成来自Web上多个异构的数据源，包括关系数据库、面向对象数据库,HTML和XML文档及结构化文本文件。在系统实现中，把Web看作是一个巨大的虚拟数据库，以CORBA作为分布式对象模型，以XML作为公共誓据模型，并且以XML-QL作为全局查询语言来完成Web上的数据查询和集成。文中还详细分析和描述了系统框架中的一些主要模块的实现方法，具有很好的可操作性。     

Translating relational schema into XML schema definition with data semantic preservation and XSD graph

Many legacy systems have been created by using relational database operating not for the Internet expression. Since the relational database is not an efficient way for data explosion, electronic transfer of data, and electronic business on the Web, we introduce a methodology in which a relational schema will be translated to an Extensible Markup Language (XML) schema definition for creating an XML database that is a simple and efficient format on the Web. We apply the Indirect Schema Translation Method that is a semantic-based methodology in this project. The mechanism is that the Relational Schema will be translated into the conceptual model, an Extended Entity Relationship (EER) Model using Reverse Engineering. Afterward, the EER model will be mapped to an XML Schema Definition Language (XSD) Graph as an XML conceptual schema using Semantic Transformation. Finally, the XSD Graph will be mapped into the XSD as an XML logical schema in the process of Forward Engineering, and the data semantics of participation, cardinality, generalization, aggregation, categorization, N-ary and U-ary relationship are preserved in the translated XML schema definition.     

Fuzzy semantic tagging and flexible querying of XML documents extracted from the Web

The relational database model is widely used in real applications. We propose a way of complementing such a database with an XML data warehouse. The approach we propose is generic, and driven by a domain ontology. The XML data warehouse is built from data extracted from the Web, which are semantically tagged using terms belonging to the domain ontology. The semantic tagging is fuzzy, since, instead of tagging the values of the Web document with one value of the domain ontology, we propose to use tags expressed in terms of a possibility distribution representing a set of possible terms, each term being weighted by a possibility degree. The querying of the XML data warehouse is also fuzzy: the end-users can express their preferences by means of fuzzy selection criteria. We present our approach on a first application domain: predictive microbiology.     

Optimizing updates of recursive XML views of relations

XML publishing has been an emerging technique for transforming (portions of) a relational database into an XML document, for example, to facilitate interoperability between heterogeneous applications. Such applications may update the XML document and the source relational database must be updated accordingly. In this paper, we consider such XML documents as (possibly) recursively defined XML views of relations. We propose new optimization techniques to efficiently support XML view updates specified via an XPATH expression with recursion and complex filters. The main novelties of our techniques are: (1) we propose a space-efficient relational encoding of recursive XML views; and (2) we push the bulk of update processing inside a relational database. Specifically, a compressed representation of the XML views is stored as extended shared-inlining relations. A space-efficient and updatable 2-hop index is used to optimize XPATH evaluation on XML views. Updates of the XML views are evaluated on these relations and index. View update translation is handled by a heuristic procedure inside a relational database, as opposed to previous middleware approaches. We present an experimental study to demonstrate the effectiveness of our proposed techniques.     

XML keyword search with promising result type recommendations

Keyword search enables inexperienced users to easily search XML database with no specific knowledge of complex structured query languages and XML data schemas. Existing work has addressed the problem of selecting data nodes that match keywords and connecting them in a meaningful way, e.g., SLCA and ELCA. However, it is time-consuming and unnecessary to serve all the connected subtrees to the users because in general the users are only interested in part of the relevant results. In this paper, we propose a new keyword search approach which basically utilizes the statistics of underlying XML data to decide the promising result types and then quickly retrieves the corresponding results with the help of selected promising result types. To guarantee the quality of the selected promising result types, we measure the correlations between result types and a keyword query by analyzing the distribution of relevant keywords and their structures within the XML data to be searched. In addition, relevant result types can be efficiently computed without keyword query evaluation and any schema information. To directly return top-k keyword search results that conform to the suggested promising result types, we design two new algorithms to adapt to the structural sensitivity of the keyword nodes over the keyword search results. Lastly, we implement all proposed approaches and present the relevant experimental results to show the effectiveness of our approach.     

基于XML数据交换的电子政务系统集成

针对政务信息化建设中存在的各种异构数据,提出一种基于XML技术的异构信息资源交换问题的实现方案。介绍方案的具体实施,详细介绍XML与关系数据库之间的映射规则,并给出具体的转换算法。该方法不仅可以反映数据的结构特征,而且还能表示数据的语义约束。研究工作在电子政务及其他信息系统的数据交换中都有一定的理论和实用价值,可为数据交换的设计提供参考。     

Efficient indexing for semantic search

The increasing performance and wider spread use of automated semantic annotation and entity linking platforms has empowered the possibility of using semantic information in information retrieval. While keyword-based information retrieval techniques have shown impressive performance, the addition of semantic information can increase retrieval performance by allowing for more accurate sense disambiguation, intent determination, and instance identification, just to name a few. Researchers have already delved into the possibility of integrating semantic information into practical search engines using a combination of techniques such as using graph databases, hybrid indices and adapted inverted indices, among others. One of the challenges with the efficient design of a search engine capable of considering semantic information is that it would need to be able to index information beyond the traditional information stored in inverted indices, including entity mentions and type relationships. The objective of our work in this paper is to investigate various ways in which different data structure types can be adopted to integrate three types of information including keywords, entities and types. We will systematically compare the performance of the different data structures for scenarios where (i) the same data structure types are adopted for the three types of information, and (ii) different data structure types are integrated for storing and retrieving the three different information types. We report our findings in terms of the performance of various query processing tasks such as Boolean and ranked intersection for the different indices and discuss which index type would be appropriate under different conditions for semantic search.     

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。     

A practical approach to extracting DTD-conforming XML documents from heterogeneous data sources

XML documents are becoming popular for business process integration. To achieve interoperability between applications, XML documents must also conform to various commonly used data type definitions (DTDs). However, most business data are not maintained as XML documents. They are stored in various native formats, such as database tables or LDAP directories. Hence, a middleware is needed to dynamically generate XML documents conforming to predefined DTDs from various data sources. As industrial consortia and large corporations have created various DTDs, it is both challenging and time-consuming to design the necessary middleware to conform to so many different DTDs. This problem is particularly acute for a small- or medium-sized enterprise because it lacks the IT skills to quickly develop such a middleware. In this paper, we present XLE, an XML Lightweight Extractor, as a practical approach to dynamically extracting DTD-conforming XML documents from heterogeneous data sources. XLE is based on a framework called DTD source annotation (DTDSA). It treats a DTD as the control structure of a program. The annotations become the program statements, such as functions and assignments. DTD-conforming XML documents are generated by parsing annotated DTDs. Basically, DTD annotations describe declaratively the mappings between target XML documents and the source data. The XLE engine implements a few basic annotations, providing a practical solution for many small- and medium-sized enterprises. However, XLE is designed to be versatile. It allows sophisticated users to plug in their own implementations to access new types of data or to achieve better performance. Heterogeneous data sources can be simply specified in the annotations. A GUI tool is provided to highlight the places where annotations are needed.     

Accommodating mesodata into conceptual modelling methodologies

Mesodata modelling is a recently developed approach for enhancing a data model’s capabilities by providing for more advanced semantics to be associated with the domain of an attribute. Mesodata supplies both an inter-value structure to the domain and a set of operations applicable to that structure that may be used to facilitate additional functionality in a database. We argue that conceptual modelling methodologies would be semantically richer if they were able to express the semantics of complex data types for attribute domains. This paper investigates the accommodation of mesodata into the entity-relationship and object role modelling, presenting the Mesodata Entity-Relationship (MDER) model and Mesodata Object Role Modelling (MDORM), which show how the mesodata concept can be incorporated into conceptual modelling methodologies to include the semantics of complex-domain structures.     

The application of data types to database semantic integrity

Data type concepts are used to investigate the extent to which database semantic integrity can be defined and ensured through database structures. Database and datatype concepts are extended mutually to improve the semantic capabilities of both database models and data type systems and to resolve apparent discrepencies between databases and programming languages. To meet database needs, data structuring is developed to form an algebra of data types. A semantically rich database model is used to show that database models can be expressed in terms of data types. Finally, a schema specification language is presented to demonstrate the power of data type tools for the definition of database schemas and for the maintenance of database semantic integrity.     

Incorporating ontology-based semantics into conceptual modelling

With the increasing complexity of applications and user needs, recent research has shifted from a data-information level to a human semantic level interaction. Research has begun to address the increasing use and development of ontologies in various applications, strongly motivated by the semantic web initiative. However, existing conceptual models are not rich enough to incorporate ontologies in one single conceptual schema. To improve this situation, it is necessary to refine modelling formalisms and make them more expressive while ensuring they remain semantically sound. We argue that conceptual modelling methodologies would be semantically richer if they were able to express the semantics of a domain that arises in concrete application scenarios. This paper investigates the incorporation of ontologies into three popular conceptual modelling methodologies, presenting the Ontological Entity-Relationship (OntoER) model, Ontological Object Role Modelling (OntoORM) and the Ontological Unified Modelling Language (OntoUML) class diagram. An extended conceptual framework for modelling ontologies and a transformation algorithm for mapping ontological constructs to relational schemata are provided so that querying the database through the conceptualisation of the database can be managed.