Fuzzy query translation for relational database systems

The paper presents a new method for fuzzy query translation based on the alpha-cuts operations of fuzzy numbers. This proposed method allows the retrieval conditions of SQL queries to be described by fuzzy terms represented by fuzzy numbers. It emphasizes friendliness and flexibility for inexperienced users. The authors have implemented a fuzzy query translator to translate user's fuzzy queries into precise queries for relational database systems. Because the proposed method allows the user to construct his fuzzy queries intuitively and to choose different retrieval threshold values for fuzzy query translation, the existing relational database systems will be more friendly and more flexible to the users.     

Example-based graphical database query languages

Several user-friendly graphical database query languages that let users formulate a query by specifying a graphically aided example on the screen are compared. One of the earliest such languages, M.M. Zloof's (1977) Query-by-Example, is described. Other languages discussed are Aggregates-by-Example, Summary-Table-by-Example, and Query-by-Statistical-Relational-Table for statistical and scientific databases; Time-by-Example for historical databases; Generalized-Query-by-Example for relational, network, and hierarchical databases; Office-by-Example, Formanager, the Natural Forms Query Language, and System-for-Business-Automation for office environments; and Picquery and Query-by-Pictorial-Example for pictorial (image) databases. The basic features, query specification and interpretation, object manipulation, query language constructs, and query processing techniques used in each of the languages are discussed     

Time-based operators for relational algebra query languages

We present a new approach for historical relational algebra languages based upon generalized logic for Boolean and comparison operators and a temporal modification of the standard relational algebra operators. Historical versions of standard (snapshot) relational algebra operators based upon this generalized logic are presented. The temporal modification employs a logic that operates on sets of value/time-interval pairs and which can be applied to snapshot as well as historical databases. Our emphasis is that the generalized operators can be used to enrich existing historical query languages and to provide an easier and more natural time-based interface. Using the generalized operators, users can express their queries more naturally, succinctly and elegantly. Examples are presented which illustrate that the modified operators offer a good degree of flexibility in expressing different temporal requirements.     

Abstract interpretation of database query languages

In this paper, we extend the Abstract Interpretation framework to the field of query languages for relational databases as a way to support sound approximation techniques. This way, the semantics of query languages can be tuned according to suitable abstractions of the concrete domain of data. The abstraction of relational database system has many interesting applications, in particular, for security purposes, such as fine grained access control, watermarking, etc.     

The expressive power of temporal relational query languages

The authors consider the representation of temporal data based on tuple and attribute timestamping. They identify the requirements in modeling temporal data and elaborate on their implications in the expressive power of temporal query languages. They introduce a temporal relational data model where N1NF relations and attribute timestamping are used and one level of nesting is allowed. For this model, a nested relational tuple calculus (NTC) is defined. They follow a comparative approach in evaluating the expressive power of temporal query languages, using NTC as a metric and comparing it with the existing temporal query languages. They prove that NTC subsumes the expressive power of these query languages. They also demonstrate how various temporal relational models can be obtained from the temporal relations by NTC and give equivalent NTC expressions for their languages. Furthermore, they show the equivalence of intervals and temporal elements (sets) as timestamps in their model     

Algebraic query optimisation for database programming languages

A major challenge still facing the designers and implementors of database programming languages (DBPLs) is that of query optimisation. We investigate algebraic query optimisation techniques for DBPLs in the context of a purely declarative functional language that supports sets as first-class objects. Since the language is computationally complete issues such as non-termination of expressions and construction of infinite data structures can be investigated, whilst its declarative nature allows the issue of side effects to be avoided and a richer set of equivalences to be developed. The language has a well-defined semantics which permits us to reason formally about the properties of expressions, such as their equivalence with other expressions and their termination. The support of a set bulk data type enables much prior work on the optimisation of relational languages to be utilised. In the paper we first give the syntax of our archetypal DBPL and briefly discuss its semantics. We then define a small but powerful algebra of operators over the set data type, provide some key equivalences for expressions in these operators, and list transformation principles for optimising expressions. Along the way, we identify some caveats to well-known equivalences for non-deductive database languages. We next extend our language with two higher level constructs commonly found in functional DBPLs: set comprehensions and functions with known inverses. Some key equivalences for these constructs are provided, as are transformation principles for expressions in them. Finally, we investigate extending our equivalences for the set operators to the analogous operators over bags. Although developed and formally proved in the context of a functional language, our findings are directly applicable to other DBPLs of similar expressiveness. Edited by Matthias Jarke, Jorge Bocca, Carlo Zaniolo. Received September 15, 1994 / Accepted September 1, 1995     

The computational completeness of extended database query languages

The computational completeness is demonstrated of certain extended database query languages, namely, POSTGRES and GENESIS, and a language defined by A. Aho and J. Ullman (1979). The method used is to implement a Turing machine interpreter in each of the languages. These query languages were defined as extensions to traditional database languages in order to encompass certain specific new applications. Results show that these extensions have already encompassed all the computational power of any programming language     

Efficient recursive XML query processing using relational database systems

Recursive queries are quite important in the context of XML databases. In addition, several recent papers have investigated a relational approach to store XML data and there is growing evidence that schema-conscious approaches are a better option than schema-oblivious techniques as far as query performance is concerned. However, the issue of recursive XML queries for such approaches has not been dealt with satisfactorily. In this paper we argue that it is possible to design a schema-oblivious approach that outperforms schema-conscious approaches for certain types of recursive queries. To that end, we propose a novel schema-oblivious approach, called Sucxent++ (Schema Unconcious XML Enabled System), that outperforms existing schema-oblivious approaches such as XParent by up to 15 times and schema-conscious approaches (Shared-Inlining) by up to eight times for recursive query execution. Our approach has up to two times smaller storage requirements compared to existing schema-oblivious approaches and 10% less than schema-conscious techniques. In addition Sucxent++ performs marginally better than Shared-Inlining and is 5.7–47 times faster than XParent as far as insertion time is concerned.     

基于关系数据库的实时XML数据查询处理

力图用成熟的关系数据库查询机制处理符合DTD的XML文档。提出了一整套数据模型、转换规则和算法描述,可以将XML文档转换为关系元组,从而达到用XML实现基于关系数据库的实时数据一致性查询处理的目的。     

Sample-based quality estimation of query results in relational database environments

The quality of data in relational databases is often uncertain, and the relationship between the quality of the underlying base tables and the set of potential query results, a type of information product (IP), that could be produced from them has not been fully investigated. This paper provides a basis for the systematic analysis of the quality of such IPs. This research uses the relational algebra framework to develop estimates for the quality of query results based on the quality estimates of samples taken from the base tables. Our procedure requires an initial sample from the base tables; these samples are then used for all possible information IPs. Each specific query governs the quality assessment of the relevant samples. By using the same sample repeatedly, our approach is relatively cost effective. We introduce the reference-table procedure, which can be used for quality estimation in general. In addition, for each of the basic algebraic operators, we discuss simpler procedures that may be applicable. Special attention is devoted to the join operation. We examine various, relevant statistical issues, including how to deal with the impact on quality of missing rows in base tables. Finally, we address several implementation issues related to sampling.     

Fuzzy multiset finite automata and their languages

Inspired by the generalizations from grammars and finite automata to fuzzy grammars and fuzzy finite automata, respectively, we introduce the concepts of fuzzy multiset grammars and fuzzy multiset finite automata (FMFAs), as the generalizations of multiset grammars and multiset finite automata, respectively. The relationship between fuzzy multiset regular grammars and FMFAs is discussed. Furthermore, we define some operations on fuzzy multiset languages, and prove that the family of FMFA languages is closed under the operations.     

Query languages for relational multidatabases

With the existence of many autonomous databases widely accessible through computer networks, users will require the capability to jointly manipulate data in different databases. A multidatabase system provides such a capability through a multidatabase manipulation language, such as MSQL. We propose a theoretical foundation for such languages by presenting a multirelational algebra and calculus based on the relational algebra and calculus. The proposal is illustrated by various queries on an example multidatabase. It is shown that properties of the multirelational algebra may be used for optimization and that every multirelational algebra query can be expressed as a multirelational calculus query. The connection between the multirelational languages and MSQL, the multidatabase version of SQL, is also investigated.     

JSON: Data model and query languages

Despite the fact that JSON is currently one of the most popular formats for exchanging data on the Web, there are very few studies on this topic and there is no agreement upon a theoretical framework for dealing with JSON. Therefore in this paper we propose a formal data model for JSON documents and, based on the common features present in available systems using JSON, we define a lightweight query language allowing us to navigate through JSON documents, study the complexity of basic computational tasks associated with this language, and compare its expressive power with practical languages for managing JSON data.     

Database query languages and functional logic programming

Functional logic programming is a paradigm which integrates functional and logic programming. It is based on the use of rewriting rules for defining programs, and rewriting for goal solving. In this context, goals, usually, consist of equality (and, sometimes, inequality) constraints, which are solved in order to obtain answers, represented by means of substitutions. On the other hand, database programming languages involve a data model, a data definition language and, finally, a query language against the data defined according to the data model. To use functional logic programming as a database programming language, (1) we will propose a data model involving the main features adopted from functional logic programming (for instance, handling of partial and infinite data), (2) we will use conditional rewriting rules as data definition language, and finally, (3) we will deal with equality and inequality constraints as query language. Moreover, as most database systems, (4) we will propose an extended relational calculus and algebra, which can be used as alternative query languages in this framework. Finally, (5) we will prove that three alternative query languages are equivalent.     

Fuzzy rough set techniques for uncertainty processing in a relational database

This paper concerns the modeling of imprecision, vagueness, and uncertainty in databases through an extension of the relational model of data: the fuzzy rough relational database, an approach which uses both fuzzy set and rough set theories for knowledge representation of imprecise data in a relational database model. The fuzzy rough relational database is formally defined, along with a fuzzy rough relational algebra for querying. Comparisons of theoretical properties of operators in this model with those in the standard relational model are discussed. An example application is used to illustrate other aspects of this model, including a fuzzy entity–relationship type diagram for database design, a fuzzy rough data definition language, and an SQL‐like query language supportive of the fuzzy rough relational database model. This example also illustrates the ease of use of the fuzzy rough relational database, which often produces results that are better than those of conventional databases since it more accurately models the uncertainty of real‐world enterprises than do conventional databases through the use of indiscernibility and fuzzy membership values. ©2000 John Wiley & Sons, Inc.