基于E-R图的关系数据库关键字查询

随着信息检索技术和数据库理论的发展,如何通过信息检索技术在关系数据库中获取有用信息,并使普通用户也可以完成在关系数据库中的关键字查询,成为近期研究人员研究的热点.基于关键字的关系数据库查询系统无需用户了解数据库模式和结构化查询语言,用户只需输入几个关键字就可以得到查询结果.基于关系数据库的原型E-R图,根据意义的不同对实体进行分组.查询时根据关键字所属关系表,确定查询的实体集合,划定查询范围,提高查询效率.提出了新的算法来提高系统的查准率.最后,通过实验对E-RKS系统效能进行验证.     

基于用户反馈的关系数据库关键字查询系统

关系数据库中的关键字查询问题使得用户无需掌握查询SQL语言与数据库模式相关知识就可以进行数据库查询,因此受到人们的广泛关注,许多方法和原型被提出.当前流行的关系数据库中关键字查询技术存在较慢的查询时间或者不准确的查询结果.针对这两个问题,提出了一种基于用户反馈的查询方法,根据用户输入的关键字动态地生成一个在数据库中包含关键字的属性所组成的Form表单提供给用户,用户在Form中进行选择并提交,最后,根据用户的选择和数据库模式图进行连接算法并执行SQL获得最终结果.     

基于历史信息提升关键字查询效率

关系数据库上的关键字查询使用户不必了解SQL语法或者数据库模式即可方便进行检索,并利用关系表的连接来保证查询的完整性.但是目前已有的关键字查询技术对于每个用户发起的查询皆从底层数据开始处理,而忽略了历史查询信息的使用.历史信息不仅包含了历史查询结果,而且反映了关键字之间的相关性,在查询过程中使用历史信息会提升查询效率.此篇论文正是针对此问题提出了新的解决方案:首先利用划分算法将用户输入的关键字划分为历史关键字和新关键字的组合;利用历史信息展开关键字查询,得到以子图形式存在的查询结果;基于与关键字的相关度对结果子图进行排序.最后,基于DBLP数据集,实验在执行时间和查准率方面证明了算法的有效性和高效性.     

半结构化数据库中的交互式查询和搜索

文章提供了对半结构数据库进行交互查询、搜索的新模型。论述了有效关键字的搜索、查询结果的结构化总结和对逆向指针支持的重要性，并针对这些技术问题给出了初步解决方案。     

关系数据库的关键词检索

SQL查询语言被用于检索关系数据库中的数据,但对于没有经验的用户来说,学习复杂的SQL语法是一件困难的事情。实现基于关键词的关系数据库信息检索,将使用户不需要任何SQL语言和底层数据库模式的知识,用搜索引擎的方式来获取数据库中的相关数据。本文总结了基于关键字的数据库检索工作的关键技术和研究进展,展望了今后的研究方向。     

Rtop-k:基于结构松弛的XML关键字近似查询方法

目前,现有的大多数关键字查询方法都是计算XML包含关键字元素的最紧致片段,这类方法大都忽略了XML文档中嵌入的结构关系,而XML结构化查询能够准确捕捉用户查询的信息,具有较高的准确率.将结构化查询方法与关键字信息检索相结合,通过分析关键字与XML文档的结构关系判断用户查询的需求,将面向对象的思想和松弛查询的方法引入到关键字查询方法中,提出一个新的XML关键字近似查询框架(Rtop-k).实验结果表明,所提近似查询方法能够较为准确地捕捉用户的查询意图,具有较高的查全率和查准率.     

RB树:一种支持空间近似关键字查询的外存索引

空间近似关键字查询包含一个空间条件和一组关键字相似性条件,这种查询在空间数据库中返回同时满足以下条件的对象:1)对象的位置信息满足查询中的空间条件;2)对于查询中的任何一个关键字,对象中至少包含一个关键字与其相似度大于给定阈值.随着当前数据的爆炸性增长,空间数据库无法完整地存放在内存中,因此空间数据库需要支持空间近似关键字查询的外存索引.目前,还没有在外存中支持精确的空间近似关键字查询的索引结构.设计了一种新型的外存索引RB树,在外存中支持精确的空间近似关键字查询.RB树支持的空间近似关键字查询包括多种空间条件,如范围查询、NN查询,同时支持多种关键字相似性度量,包括编辑距离、规范化编辑距离等.通过真实数据中的性能测试验证了RB树的效率.     

多关键字云资源搜索算法

云计算的核心是在虚拟化技术的基础上,通过互联网技术为用户提供动态易扩展的计算资源。利用中心服务器的计算模式来管控网络上大量云资源使得中心服务器成为整个系统的瓶颈,不利于云计算的大规模应用,因此提出使用对等网络技术构建分布式的云资源索引存储和查询系统,但是结构化拓扑系统维护比较复杂,一般不支持复杂搜索条件查询。本文提出了一种多关键字云资源搜索算法。在基于分层超级节点的云资源搜索算法基础上进行路由算法改进,希望实现多关键字的精确查询。对多关键字的生成、分割及存储做出了详细说明,提出一种有效的基于数据集的索引搜索策略,实现了包含三个或三个以上的关键字高效、准确查询。分析实验结果证明了算法明显提高了资源搜索的命中率,尤其是随着关键字数目的增多,不仅保证了资源搜索的命中率,同时大大增加了资源的召回率。     

基于关系数据库的top-k聚合关键词查询

基于关系数据库的关键词查询,使得用户在不需要掌握结构化查询语言和数据库模式的情况下,可以方便地进行关系数据库查询.给定一个关键词查询,已有的方法通过数据库中的主外键关联,查询得到包含关键词的元组集合.但是,在很多实际应用中,元组集合的聚合结果对用户更有价值;研究了基于关系数据库的top-k聚合关键词查询,提出了基于递归的聚合单元枚举算法——基于递归的完全搜索(recursion-based full search,RFS).为了获得更好的查询性能,设计了新的排序方法、二维索引和快速搜索算法——基于输出的快速搜索(output-based quick search,OQS),从而可以高效地枚举top-k个聚合单元;在不同的数据集上进行了大量的实验,实验结果表明OQS算法具有良好的查询性能.     

空间关键字个性化语义近似查询方法

现有的空间关键字查询处理模式大都仅支持位置相近和文本相似匹配,但不能将语义相近但形式上不匹配的对象提供给用户;并且,当前的空间-文本索引结构也不能对空间对象中的数值属性进行处理。针对上述问题,本文提出了一种支持语义近似查询的空间关键字查询方法。首先,利用词嵌入技术对用户原始查询进行扩展,生成一系列与原始查询关键字语义相关的查询关键字;然后,提出了一种能够同时支持文本和语义匹配,并利用Skyline方法对数值属性进行处理的混合索引结构AIR-Tree;最后,利用AIR-Tree进行查询匹配,返回top-k个与查询条件最为相关的有序空间对象。实验分析和结果表明,与现有同类方法相比,本文方法具有较高的执行效率和较好的用户满意度;基于AIR-Tree索引的查询效率较IRS-Tree索引提高了3.6%,在查询结果准确率上较IR-Tree和IRS-Tree索引分别提高了10.14%和16.15%。     

PICASSO: A graphical query language

PICASSO (PICture Aided Sophisticated Sketch Of database queries) is a graphics-based database query language designed for use with a universal relation database system. The primary objective of PICASSO is ease of use. Graphics are used to provide a simple method of expressing queries and to provide visual feedback to the user about the system's interpretation of the query. Inexperienced users can use the graphical feedback to aid them in formulating queries whereas experienced users can ignore the feedback. Inexperienced users can pose queries without knowing the details of underlying database schema and without learning the formal syntax of SQL-like query language. This paper presents the syntax of PICASSO queries and compares PICASSO queries with similar queries in standard relational query languages. Comparisons are also made with System/U, a non-graphical universal relation system on which PICASSO is based. The hypergraph semantics of the universal relation are used as the foundation for PICASSO and their integration with a graphical workstation enhances the usability of database systems.     

Making Database Schema Hierarchical for Visual Access to Databases

Making the database schema hierarchical can help a casual user retrieve information from a complex database. The hierarchical database schema provides further insight into database content and focuses on meaningful data by a top-down method. The user can proceed with a hierarchical visual query, which ultimately simplifies the query, reduces the syntax error rate and conserves the query time. In this paper, we present a hierarchical graph which makes the database schema hierarchical, naturally integrates the browsing and querying and, consequently, allows the user to proceed with an incremental query on the hierarchical database schema. Also proven herein are the existence, uniformity, and consistency of the hierarchical graph to verify that the graph can be used to query the database. This paper also discusses the semantics of high-level nodes and conducts an experiment to evaluate users’ performance. Finally, we describe how one can use the hierarchical graph to unify the tasks of making the schema hierarchical, creating concept hierarchies, and integrating the databases.     

HVQS: The Hierarchical Visual Query System for Databases

This work describes the design and implementation of hierarchical visual query system (HVQS). It is a user interface for querying and browsing databases in a hierarchical database schema. HVQS enables users to use ahierarchical visual query , i.e. they can visually formulate a query and watch the query results on a few higher layers of database schema. This simplifies the query, reduces the failure rate, conserves query time, allows users to work on a database schema with wider scope, and helps users understand database content and focus on meaningful data using a top-down method. This work first gives an overview of the hierarchical visual query, and then describes the prototype of HVQS, defines a hierarchical graph for representing hierarchical database schema, and discusses the Query Manager and Visual Interface Manager of HVQS. Also described herein is the expressive power and semantics of HVQS query. Finally, a evaluation report of an experiment is given to demonstrate that HVQS improves the query success rate and facilitates users in query formulation.     

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.     

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.     

A data model and a query languagefor multimedia documents databases

A multimedia application involves information that may be in a form of video, images, audio, text and graphics, need to be stored, retrieved and manipulated in large databases. In this paper, we propose an object-oriented database schema that supports multimedia documents and their temporal, spatial and logical structures. We present a document example and show how the schema can adress all the structures described. We also present a multimedia query specification language that can be used to describe a multimedia content portion to be retrieved from the database. The language provides means by which the user can specify the information on the media as well as the temoral and spatial relationships among these media.     

Producing Interoperable Queries for Relational and Object-Oriented Databases

In this paper, we develop techniques to produce interoperable queries with object and relational databases. A user poses a local query in a local query language, against a local object or relational schema. We transparently produce appropriate queries with respect to a remote target object or relational schema, corresponding to some remote database which contains data relevant to the user's query. Mapping knowledge to resolve representational heterogeneities in local and remote schemas is expressed in a canonical representation, CRmapping, and is independent of the particular data model. A canonical representation CRquery is also used to resolve heterogeneities of query languages. A set of heterogeneous transformation algorithms define the appropriate transformations from the local queries to the remote queries. The use of canonical representations (CR) allows us to represent queries independent of the particular query language, and to resolve representational conflicts in a uniform manner, independent of models and query languages.     

Formalizing visual interaction with historical databases

Recent database applications are typically oriented towards a large set of non-expert users, and therefore, they need to be equipped with suitable interfaces facilitating the interaction with the system. Moreover, the incorporation of the time dimension in database systems is a desirable feature. Indeed, several temporal data models and the corresponding textual query languages have been proposed. However, there is a limited amount of research concerning the investigation of user-oriented languages for querying temporal databases. Our proposal addresses such a need. In particular, we propose a visual query environment, namely Temporal Visual Query Environment (TVQE) which provides an easier interaction of the user with temporal databases. The system adopts a diagrammatic representation of the database schema (including temporal classes and relationships) and a “graphical notebook” as interaction metaphor. In our approach, non-database experts are released from syntactical difficulties which are typical of textual languages, and they can easily express temporal queries by means of elementary graphical operations (e.g. click on a node label). Differently from many proposals in the field of visual query languages, the language underlying TVQE is provided with formal syntax and semantics. It is based on a minimal set of temporal graphical primitives (TGPs), which are defined on a Temporal Graph Model (TGM), with visual syntax and object-based semantics. In this paper we mainly concentrate on the formal aspects of TVQE, and provide some hints on the visual interaction mechanisms and implementation issues.     

VIREX and VRXQuery: interactive approach for visual querying of relational databases to produce XML

VIREX provides an interactive approach for querying and integrating relational databases to produce XML documents and the corresponding schemas. VIREX connects to each database specified by the user; analyzes the catalogue to derive an interactive diagram equivalent to the extended entity-relationship diagram; allows the user to display sample records from the tables in the database; allows the user to rename columns and relations by modifying directly the interactive diagram; facilitates the conversion of the relational database into XML; and derives the XML schema. VIREX works even when the catalogue of the relational database is missing; it extracts the required catalogue information by analyzing the database content. Further, VIREX supports VRXQuery, which is a visual naive-users-oriented query language that allows users to specify queries and define views directly on the interactive diagram as a sequence of mouse clicks with minimum keyboard input. The user is expected to interactively decide on certain factors to be considered in producing the XML result. Such factors include: 1) selecting the relations/attributes to be converted into XML; 2) specifying a predicate to be satisfied by the information to be converted into XML; 3) deciding on the order of nesting between the relations to be converted into XML; 4) ordering for the result. VRXQuery supports selection, projection, nesting/join, union, difference, and order-by. As the result of a query, VIREX displays on the screen the XML schema that satisfies the specified characteristics and generates colored (easy to read) XML document(s). Further, VIREX allows the user to display and review the SQL and XQuery equivalent to each query expressed in VRXQuery.