Adequate Sets of Temporal Connectives in CTL

An adequate set of temporal connectives for CTL is a subset of the logic's temporal connectives that is sufficient to express equivalents for all CTL formulas.In this paper, a characterization of all such adequate sets is presented. Specifically, it is shown that a subset of CTL's temporal connectives is adequate if and only if it contains one of {AX, EX}, one of {EG, AF, AU}, and EU.The proof requires, among other things, the analysis of a certain class of models, the reflexive models. These models have the desirable property that several connectives become redundant, thus simplifying the analysis.     

Query Optimization for Deductive Databases

A systematic,efficient compilation method for query evaluation of Deductive Databases (DeDB) is proposed in this paper.In order to eliminate redundancy and to minimize the potentially relevant facts,which are two key issues to the efficiency of a DeDB,the compilation process is decomposed into two phases.The first is the pre-compilation phase,which is responsible for the minimization of the potentially relevant facts.The second,which we refer to as the general compilation phase,is responsible for the elimination of redundancy.The rule/goal graph devised by J.D.Ullman is appropriately extended and used as a uniform formalism.Two general algorithms corresponding to the two phases respectively are described intuitively and formally.     

Ranked Query Processing in Uncertain Databases

Recently, many new applications, such as sensor data monitoring and mobile device tracking, raise up the issue of uncertain data management. Compared to "certain” data, the data in the uncertain database are not exact points, which, instead, often reside within a region. In this paper, we study the ranked queries over uncertain data. In fact, ranked queries have been studied extensively in traditional database literature due to their popularity in many applications, such as decision making, recommendation raising, and data mining tasks. Many proposals have been made in order to improve the efficiency in answering ranked queries. However, the existing approaches are all based on the assumption that the underlying data are exact (or certain). Due to the intrinsic differences between uncertain and certain data, these methods are designed only for ranked queries in certain databases and cannot be applied to uncertain case directly. Motivated by this, we propose novel solutions to speed up the probabilistic ranked query (PRank) with monotonic preference functions over the uncertain database. Specifically, we introduce two effective pruning methods, spatial and probabilistic pruning, to help reduce the PRank search space. A special case of PRank with linear preference functions is also studied. Then, we seamlessly integrate these pruning heuristics into the PRank query procedure. Furthermore, we propose and tackle the PRank query processing over the join of two distinct uncertain databases. Extensive experiments have demonstrated the efficiency and effectiveness of our proposed approaches in answering PRank queries, in terms of both wall clock time and the number of candidates to be refined.     

粗关系数据库查询模型

针对粗关系数据库中数据的特性,提出一种不确定性数据的存储方法。基于汉明距离的一种变式,计算元组间距离,构成距离矩阵,根据距离矩阵将相同或相近的元组归类,从而有效地对表中的元组进行索引。借助粗集中的上、下近似,通过计算用户查询的数据与粗关系数据库中数据的相似度,查询出用户所需的数据。结合以上方法构建粗关系数据库查询模型,设计相应的查询算法并应用于实例中。     

非一致性数据库的概率查询重写

结合概率数据库技术,以元组匹配所产生的聚类为基础,提出了一种新的基于聚类的非一致性数据的概率方法。基于可信聚类,给出了基本的查询重写技术,在有聚集的查询中,考虑了合适的元组概率、区间值、期望值。在不进行程序预处理的情况下,“重写”能被商业数据库系统有效地优化和执行,采用不一致性数据的区分度和数据库大小去理解其适应性,并使用了TPC-H基准的数据和查询。实验显示了该方法的有效性。     

基于Vague数据库的代数查询语言

基于Vague集理论的Vague关系数据库与其他模糊数据库一样,由于所含信息的模糊性,对应着现实世界的多种状态.虽然此类数据库能够更加真实地反映现实世界,但是在基于这些数据库的查询语言的有效性和计算过程的复杂性等方面却存在着一定的问题.本文基于Vague关系数据模型,对其代数查询语言中的选择、投影和连接操作进行了研究,指出基于一般Vague关系数据模型的查询语言中所存在的问题,并提出相应的解决方法,引入一种嵌套机制,对Vague关系模型进行了进一步扩展,进而对新模型查询语言中的三种操作在不同情况下进行了讨论,并给出了相应的定义.     

Optimal-Location-Selection Query Processing in Spatial Databases

This paper introduces and solves a novel type of spatial queries, namely, Optimal-Location-Selection (OLS) search, which has many applications in real life. Given a data object set D_A, a target object set D_B, a spatial region R, and a critical distance d_c in a multidimensional space, an OLS query retrieves those target objects in D_B that are outside R but have maximal optimality. Here, the optimality of a target object b in D_B located outside R is defined as the number of the data objects from D_A that are inside R and meanwhile have their distances to b not exceeding d_c. When there is a tie, the accumulated distance from the data objects to b serves as the tie breaker, and the one with smaller distance has the better optimality. In this paper, we present the optimality metric, formalize the OLS query, and propose several algorithms for processing OLS queries efficiently. A comprehensive experimental evaluation has been conducted using both real and synthetic data sets to demonstrate the efficiency and effectiveness of the proposed algorithms.     

非一致性数据库的多关系聚集查询重写

基于非一致性关系数据库的选择连接查询技术,提出了基于非一致性数据库多个关系上的聚集查询重写方法.该聚集查询重写方法先通过查询出多关系上的一致性结果.然后进行分组聚集,返回聚集表达范围边界值.实验采用TPC-H决策支持基准进行性能研究,结果表明重写查询比初始查询的执行时间要长,但还是可以接受的,因此该方法是有效的.     

追加型数据库外包中的查询结果验证

数据库外包是将数据库管理工作外包给专业第三方,而数据库外包中需要解决的关键问题之一是查询结果的验证.提出了外包追加型数据库的问题.根据外包追加型数据库的特点,在现有验证数据结构的基础上,提出了一种新型验证数据结构Min-Max Hash Tree,可以有效地解决客户对查询结果进行验证的问题.对于数据所有者端,给出了基本的数据发送算法;对于服务提供商端,分别给出了一次性查询和连续查询的查询算法和查询结果验证算法.最后,对数据所有者端的验证数据结构的存储、数据发送和服务提供商端的连续查询进行了优化处理,大大节省了数据所有者端的存储空间,提高了数据的整体处理效率.实验表明,Min-Max Hash Tree能够有效完成追加型数据库外包的查询结果验证,并且能够高效率处理大规模数据.     

时空数据库中多个最近邻对象的查询算法

在时空数据库中，最近邻查询用于对某个查询对象，在被查询对象中找出离它最近的一个或多个对象。该文在TPR树这一时空索引的基础上，提出了一种高效的最近邻查询算法，能够支持移动对象的多个最近邻对象的查询，并在性能上也有所提高。     

Fast Nearest-Neighbor Query Processing in Moving-Object Databases

A desirable feature in spatio-temporal databases is the ability to answer future queries, based on the current data characteristics (reference position and velocity vector). Given a moving query and a set of moving objects, a future query asks for the set of objects that satisfy the query in a given time interval. The difficulty in such a case is that both the query and the data objects change positions continuously, and therefore we can not rely on a given fixed reference position to determine the answer. Existing techniques are either based on sampling, or on repetitive application of time-parameterized queries in order to provide the answer. In this paper we develop an efficient method in order to process nearest-neighbor queries in moving-object databases. The basic advantage of the proposed approach is that only one query is issued per time interval. The time-parameterized R-tree structure is used to index the moving objects. An extensive performance evaluation, based on CPU and I/O time, shows that significant improvements are achieved compared to existing techniques.     

密文数据库查询优化技术①

为了解决数据库加密后查询效率低的问题,针对数据库加密技术的实际应用,提出了一些解决方案。通过对数值型密文数据使用标志位,为字符型数据创建外存索引文本,缩小了查询范围,提高了数据查询效率。最后进行实验测试分析,证实了方法的有效性。     

非一致性数据库的多关系聚集查询重写

基于非一致性关系数据库的选择连接查询技术,提出了基于非一致性数据库多个关系上的聚集查询重写方法。该聚集查询重写方法先通过查询出多关系上的一致性结果,然后进行分组聚集,返回聚集表达范围边界值。实验采用TPC-H策支持基准进行性能研究,结果表明重写查询比初始查询的执行时间要长,但还是可以接受的,因此该方法是有效的。     

不确定数据库中的阈值轮廓查询处理

传统轮廓查询算法都没有考虑不确定数据的特殊性质,因而不能直接应用到不确定数据应用中.深入地研究了不确定数据库中的轮廓查询处理技术.首先,提出了不确定数据库中阈值轮廓查询的定义;其次,通过对其性质的分析,提出了基于R一树索引的基本的阈值轮廓算法(BPS);接着,通过对其性质的进一步分析,在BPS算法的基础上,增加了有效的过滤策略,提出了改进的阈值轮廓算法(IPS).实验结果表明,IPS算法可以有效地减少阈值轮廓的计算时间,从而满足实际应用的性能需求.     

Toward Practical Query Evaluation for Constraint Databases

Linear constraint databases (LCDBs) extend relational databases to include linear arithmetic constraints in both relations and queries. A LCDB can also be viewed as a powerful extension of linear programming (LP) where the system of constraints is generalized to a database containing constraints and the objective function is generalized to a relational query containing constraints. Our major concern is query optimization in LCDBs. Traditional database approaches are not adequate for combination with LP technology. Instead, we propose a new query optimization approach, based on statistical estimations and iterated trials of potentially better evaluation plans. The resulting algorithms are not only effective on LCDBs, but also applicable to existing query languages. A number of specific constraint algebra algorithms are also developed: select-project-join for two relations, constraint sort-join and constraint multi-join.     

基于关系数据库的模糊查询技术

在关系数据库中,SQL只能处理精确查询,而现实中存在许多模糊查询的问题。在模糊逻辑理论的基础上,提出了关系数据库的模糊查询思路,并详细地讨论了在数值和字符属性上的实现方法。实现方法不仅对数据库的查询进行了扩展,而且对实际系统的开发也有一定的借鉴作用。