Web信息集成系统中查询的处理

为了有效地实现对Web上异构数据源的统一查询处理,提出了一个基于本体的异构数据源集成系统模型OBIISM,引入本体解决各数据源语义层上的异构,通过两级查询重写将用户提交的查询转化为对数据源的查询,为查询异构数据源提供了一个语义统一的接口.     

数据集成中XML数据查询语义重写

查询重写是数据库研究的一个基本问题，它和查询优化，数据仓库，数据集成，语义缓存等数据库问题密切相关，为提高集成系统的查询效率，系统选择提交频率较高的XML查询物化为中间层视图，用户提交查询后，系统尽可能利用中间视图层中视图，而不是访问数据源来回答查询，这个问题实际可以归结为半结构化查询重写问题，考虑到中间视图层空间的有限性，已有视图应当尽可能回答更多的查询，传统查询重写方法有考虑半结构化数据之间的约束，而根据约束可以等价变换查询，从而提高中间视图层中的表达能力，提出了一种新的半结构化查询重写的方法，该方法在保证算法正确性和完备性的基础上，利用上半结构化数据中的约束，尤其是XML文件中的路径依赖，来增强中间层物化视图的表达能力，理论分析和初步原型实验证明方法的有效性。     

A graphical query language: VISUAL and its query processing

This paper describes VISUAL, a graphical icon-based query language with a user-friendly graphical user interface for scientific databases and its query processing techniques. VISUAL is suitable for domains where visualization of the relationships is important for the domain scientist to express queries. In VISUAL, graphical objects are not tied to the underlying formalism; instead, they represent the relationships of the application domain. VISUAL supports relational, nested, and object-oriented models naturally and has formal basis. For ease of understanding and for efficiency reasons, two VISUAL semantics are introduced, namely, the interpretation and execution semantics. Translations from VISUAL to the Object Query Language (for portability considerations) and to an object algebra (for query processing purposes) are presented. Concepts of external and internal queries are developed as modularization tools.     

Foundations for object-oriented query processing

A minimal framework for an object-oriented query language standard should (1) include a formal definition of a high-level data model and the syntax and semantics of associated query languages, (2) provide the functionality of relational query languages, and (3) support proofs of correctness of transformations for logical query optimization. In this paper, a high-level conceptual model for object-oriented query processing is discussed; the model includes widely-used structural abstractions such as the isa relationship, associations (properties) between complex objects and complex objects/values, and inheritance of properties. A formal, algebraic query language for the model, inspired by relational algebra, is presented. Operators of the algebra allow queries based on values, queries that manipulate entire objects, and queries that construct new objects from existing objects/values. All queries retain connections to existing database objects, providing logical access paths to data. Each query result is a class, so the algebra has the closure property. The intensional and extensional results of query operators are summarized. Two forms of logical query optimization supported by the query algebra are outlined: algebraic transformations and classifier-based optimizations (optimizations which employ inclusion and exclusion dependencies between classes).     

A research agenda for query processing in large-scale peer data management systems

Peer Data Management Systems (Pdms) are a novel, useful, but challenging paradigm for distributed data management and query processing. Conventional integrated information systems have a hierarchical structure with an integration component that manages a global schema and distributes queries against this schema to the underlying data sources. Pdms are a natural extension to this architecture by allowing each participating system (peer) to act both as a data source and as an integrator. Peers are interconnected by schema mappings, which guide the rewriting of queries between the heterogeneous schemas, and thus form a P2P (peer-to-peer)-like network.Despite several years of research, the development of efficient Pdms still holds many challenges. In this article we first survey the state of the art on peer data management: We classify Pdms by characteristics concerning their system model, their semantics, their query planning schemes, and their maintenance. Then we systematically examine open research directions in each of those areas. In particular, we observe that research results from both the domain of P2P systems and of conventional distributed data management can have an impact on the development of Pdms.     

深层网查询接口的自动集成

深层网数据库的访问方式主要是通过查询接口,所以查询接口是外部访问深层网数据库的门户.为了能够同时访问同一领域多个Web数据库,需要对多个Web数据库的查询接口进行集成.因此,提出基于本体的深层网查询接口集成方法.首先构建领域核心本体,在模式匹配过程中,不断完善核心本体;然后,以本体作为媒介,在不同查询接口模式间建立属性映射关系,发现属性间的语义关联;最后,根据本体概念出现的频数生成集成接口.实验表明提出的深层网查询接口自动集成方法是可行的和高效的.     

概率Top-κ查询的层次索引

由于在经济、军事等领域的广泛应用,不确定数据的查询处理技术成为近年来数据库领域的研究热点.概率top-κ查询根据打分函数和概率两个维度来对数据进行排序,因此具有多种查询语义.作为I/O密集型查询,概率top-κ查询需要具备一定通用性的索引技术来提高查询效率.本文从分析概率top-κ查询满足的性质入手,分别基于skyline和支配频率的概念,提出两种层次索引.通过理论分析和实验证明了满足特定性质的概率top-κ查询均可以利用这两种索引来提高I/O效率,其中基于支配频率的索引具有更好的鲁棒性.     

Supporting web query expansion efficiently using multi-granularity indexing and query processing

The problem of word mismatch in information retrieval (IR) occurs because users often use different words to describe concepts in their queries than authors use to describe the same concepts in their documents. Query expansion is used to deal with the mismatch between author and user vocabularies. To support query expansion, indices on words related by lexical semantics and syntactical co-occurrence need to be maintained. Two issues become paramount in supporting query expansion: the size of index tables and the query processing overhead. In this paper, we propose to use the notion of multi-granularity for more efficient indexing and query processing while the same degrees of precision and recall are maintained. We also describes extensions of this technique to handle: (1) query relaxation to handle words with multiple senses and with other semantic relationships; (2) progressive processing of queries with top N results and (3) progressive processing of queries with specification of the importance of each keyword.     

Query rewritings using views for XPath queries,framework, and methodologies

Query rewriting using views is a technique that allows a query to be answered efficiently by using pre-computed materialized views. It has many applications, such as data caching, query optimization, schema integration, etc. This issue has been studied extensively for relational databases and, as a result, the technology is maturing. For XML data, however, the work is inadequate. Recently, several frameworks have been proposed for query rewriting using views for XPath queries, with the requirement that a rewriting must be complete. In this paper, we study the problem of query rewriting using views for XPath queries without requiring that the rewriting be complete. This will increase its applicability since in many cases, complete rewritings using views do not exist. We give formal definitions for various concepts to formulate the problem, and then propose solutions. Our solutions are built under the framework for query containment. We look into the problem from both theoretic perspectives, and algorithmic approaches. Two methods to generate rewritings using views are proposed, with different characteristics in terms of generalities and efficiencies. The maximality properties of the rewritings generated by these methods are discussed.     

Bayesian networks for supporting query processing over incomplete autonomous databases

As the information available to naïve users through autonomous data sources continues to increase, mediators become important to ensure that the wealth of information available is tapped effectively. A key challenge that these information mediators need to handle is the varying levels of incompleteness in the underlying databases in terms of missing attribute values. Existing approaches such as QPIAD aim to mine and use Approximate Functional Dependencies (AFDs) to predict and retrieve relevant incomplete tuples. These approaches make independence assumptions about missing values—which critically hobbles their performance when there are tuples containing missing values for multiple correlated attributes. In this paper, we present a principled probabilistic alternative that views an incomplete tuple as defining a distribution over the complete tuples that it stands for. We learn this distribution in terms of Bayesian networks. Our approach involves mining/“learning” Bayesian networks from a sample of the database, and using it to do both imputation (predict a missing value) and query rewriting (retrieve relevant results with incompleteness on the query-constrained attributes, when the data sources are autonomous). We present empirical studies to demonstrate that (i) at higher levels of incompleteness, when multiple attribute values are missing, Bayesian networks do provide a significantly higher classification accuracy and (ii) the relevant possible answers retrieved by the queries reformulated using Bayesian networks provide higher precision and recall than AFDs while keeping query processing costs manageable.     

面向PSTP查询的高效处理算法

在使用"不完全结构的约束查询(PSTP查询)"从XML文档中获取信息时,用户可以根据自身对XML文档结构的熟悉程度,在查询表达式中灵活地嵌入结构约束条件,从而满足完全不了解、完全了解及了解部分结构信息的各种用户的查询需求。提出一种基于扩展Dewey编码的查询处理算法,可以在仅扫描一遍元素的情况下,处理任意形式的PSTP查询。不同数据集上的实验结果表明,EDPS算法在处理twig查询、不包含"*"结点的PSTP查询及包含"*"结点的PSTP查询时,综合性能明显优于已有方法。     

Efficient processing of top-k dominating queries in distributed environments

Due to the recent massive data generation, preference queries are becoming an increasingly important for users because such queries retrieve only a small number of preferable data objects from a huge multi-dimensional dataset. A top-k dominating query, which retrieves the k data objects dominating the highest number of data objects in a given dataset, is particularly important in supporting multi-criteria decision making because this query can find interesting data objects in an intuitive way exploiting the advantages of top-k and skyline queries. Although efficient algorithms for top-k dominating queries have been studied over centralized databases, there are no studies which deal with top-k dominating queries in distributed environments. The recent data management is becoming increasingly distributed, so it is necessary to support processing of top-k dominating queries in distributed environments. In this paper, we address, for the first time, the challenging problem of processing top-k dominating queries in distributed networks and propose a method for efficient top-k dominating data retrieval, which avoids redundant communication cost and latency. Furthermore, we also propose an approximate version of our proposed method, which further reduces communication cost. Extensive experiments on both synthetic and real data have demonstrated the efficiency and effectiveness of our proposed methods.     

DIASPORA: A highly distributed web-query processing system

Current proposals for web querying systems have assumed a centralized processing architecture wherein data is shipped from the remote sites to the user's site. We present here the design and implementation of DIASPORA, a highly distributed query processing system for the web. It is based on the premise that several web applications are more naturally processed in a distributed manner, opening up possibilities of significant reductions in network traffic and user response times. DIASPORA is built over an expressive graph-based data model that utilizes simple heuristics and lends itself to automatic generation. The model captures both the content of web documents and the hyperlink structural framework of a web site. Distributed queries on the model are expressed through a declarative language that permits users to explicitly specify navigation. DIASPORA implements a query-shipping model wherein queries are autonomously forwarded from one web-site to another, without requiring much coordination from the query originating site. Its design addresses a variety of interesting issues that arise in the distributed web context including determining query completion, handling query rewriting, supporting query termination and preventing multiple computations of a query at a site due to the same query arriving through different paths in the hyperlink framework. The DIASPORA system is currently operational and is undergoing testing on our campus network. In this paper we describe the design of the system and report initial performance results that indicate significant performance improvements over comparable centralized approaches. This revised version was published online in August 2006 with corrections to the Cover Date.     

Extending the UML concepts to transform natural language queries with fuzzy semantics into SQL

Database applications tend toward getting more versatile and broader to comply with the expansion of various organizations. However, naïve users usually suffer from accessing data arbitrarily by using formal query languages. Therefore, we believe that accessing databases using natural language constructs will become a popular interface in the future. The concept of object-oriented modeling makes the real world to be well represented or expressed in some kinds of logical form. Since the class diagram in UML is used to model the static relationships of databases, in this paper, we intend to study how to extend the UML class diagram representations to capture natural language queries with fuzzy semantics. By referring to the conceptual schema throughout the class diagram representation, we propose a methodology to map natural language constructs into the corresponding class diagram and employ Structured Object Model (SOM) methodology to transform the natural language queries into SQL statements for query executions. Moreover, our approach can handle queries containing vague terms specified in fuzzy modifiers, like ‘good’ or ‘bad’. By our approach, users obtain not only the query answers but also the corresponding degree of vagueness, which can be regarded as the same way we are thinking.     

Query rewriting using views in the presence of functional and inclusion dependencies

Query rewriting using views is a technique for determining how a query may be answered using a given set of resources, which may include materialized views, cached results of previous queries, or queries answerable by other databases. The power of query rewriting can be considerably enhanced by taking into account integrity constraints that are known to hold on base relations. This paper describes an extension of query rewriting that utilizes inclusion dependencies to find rewritings of queries that would otherwise be overlooked. We describe a complete strategy for finding rewritings in the presence of inclusion dependencies and present a basic algorithm that implements that strategy. We also describe extensions to this algorithm when both inclusion and functional dependencies are considered.     

异构数据源集成应用模型及其查询处理方法

异构数据源联合使用的目的是屏蔽数据源的异构性，提供给用户一个使用多种数据源的统一接口，在实现联合使用的系统中的难点是用户查询的重写和分解。该文介绍了基于半结构化数据模型的异构数据源联合使用的实现，描述了其中的查询重写和查询分解的方法。     

AnyQuery:网格环境下基于服务的分布式查询处理系统

AnyQuery是一种适用于网格环境、基于服务的分布式查询处理系统，使用统一的数据格式（可扩展标记语言）来表示和传输数据，所有组成模块以网格服务的形式实现，网格服务之间通过标准的接口进行通信．这种接口和实现分离技术屏蔽了不同数据库及其运行节点的差异，为用户提供一致的虚拟关系数据视图和分布式数据查询支持．在分析和研究已有的并行数据库和分布式数据库查询技术的基础上，AnyQuery提出和实现了一种适用于动态网格环境的分布式查询计划生成和执行算法，该算法能够根据网格环境中各节点及其连接网络的实际情况确定查询计划，支持跨数据库的连接查询．基于Globus 3．0开发了AnyQuery的原型系统，性能测试表明该系统具有较好的可扩展性，尤其适合计算密集型的复杂查询．     

Querying through a user interface

In contrast to a traditional setting where users express queries against the database schema, we assert that the semantics of data can often be understood by viewing the data in the context of the user interface (UI) of the software tool used to enter the data. That is, we believe that users will understand the data in a database by seeing the labels, drop-down menus, tool tips, or other help text that are built into the user interface. Our goal is to allow domain experts with little technical skill to understand and query data. In this paper, we present our GUi As View (Guava) framework and describe how we use forms-based UIs to generate a conceptual model that represents the information in the user interface. We then describe how we generate a query interface from the conceptual model. We characterize the resulting query language using a subset of the relational algebra. Since most application developers want to craft a physical database to meet desired performance needs, we present here a transformation channel that can be configured by instantiating one or more of our transformation operators. The channel, once configured, automatically transforms queries from our query interface into queries that address the underlying physical database and delivers query results that conform to our query interface. In this paper, we define and formalize our database transformation operators. The contributions of this paper are that first, we demonstrate the feasibility of creating a query interface based directly on the user interface and second, we introduce a general purpose database transformation channel that will likely shorten the application development process and increase the quality of the software by automatically generating software artifacts that are often made manually and are prone to errors.