Object-oriented query language access to relational databases: A semantic framework for query translation

This research investigates and approach to query processing in a multidatabase system that uses an objectoriented model to capture the semantics of other data models. The object-oriented model is used to construct a global schema, defining an integrated view of the different schemas in the environment. The model is also used as a self-describing model to build a meta-database for storing information about the global schema. A unique aspect of this work is that the object-oriented model is used to describe the different data models of the multidatabase environment, thereby extending the meta database with semantic information about the local schemas. With the global and local schemas all represented in an object-oriented form, structural mappings between the global schema and each local schema are then easily supported. An object algebra then provides a query language for expressing global queries, using the structural mappings to translate object algebra queries into SQL queries over local relational schema. The advantage of using an object algebra is that the object-oriented database can be viewed as a blackboard for temporary storage of local data and for establishing relationships between different databases. The object algebra can be used to directly retrieve temporarily-stored data from the object-oriented database or to transparently retrieve data from local sources using the translation process described in this paper.     

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.     

Taxonomy-based relaxation of query answering in relational databases

Traditional information search in which queries are posed against a known and rigid schema over a structured database is shifting toward a Web scenario in which exposed schemas are vague or absent and data come from heterogeneous sources. In this framework, query answering cannot be precise and needs to be relaxed, with the goal of matching user requests with accessible data. In this paper, we propose a logical model and a class of abstract query languages as a foundation for querying relational data sets with vague schemas. Our approach relies on the availability of taxonomies, that is, simple classifications of terms arranged in a hierarchical structure. The model is a natural extension of the relational model in which data domains are organized in hierarchies, according to different levels of generalization between terms. We first propose a conservative extension of the relational algebra for this model in which special operators allow the specification of relaxed queries over vaguely structured information. We also study equivalence and rewriting properties of the algebra that can be used for query optimization. We then illustrate a logic-based query language that can provide a basis for expressing relaxed queries in a declarative way. We finally investigate the expressive power of the proposed query languages and the independence of the taxonomy in this context.     

Unacceptable components in fuzzy relational databases

The existence of unacceptable components, which consist of unacceptable tuples and elements in attribute values, is shown in fuzzy relational databases. The unacceptable components are created by update operations, insertion, deletion, and modification. An unacceptable tuple in a relation is a tuple such that the degree of its not belonging to that relation is greater than that of its belonging to. The unacceptable tuple can be easily eliminated from relations. There are three kinds of unacceptable elements. One case of unacceptable elements is a redundant element created by insertion and modification. Another is an element created by a possible tuple value not at all or partially satisfying integrity constraints in insertion and modification. The other is an element created by a possible tuple value completely or partially satisfying update conditions in deletion. The unacceptable elements can be eliminated from relations without loss of information. As a result, we can obtain fuzzy relational databases without unacceptable components by a reasonable way. © 1996 John Wiley & Sons, Inc.     

Prioritized repairing and consistent query answering in relational databases

A consistent query answer in an inconsistent database is an answer obtained in every (minimal) repair. The repairs are obtained by resolving all conflicts in all possible ways. Often, however, the user is able to provide a preference on how conflicts should be resolved. We investigate here the framework of preferred consistent query answers, in which user preferences are used to narrow down the set of repairs to a set of preferred repairs. We axiomatize desirable properties of preferred repairs. We present three different families of preferred repairs and study their mutual relationships. Finally, we investigate the complexity of preferred repairing and computing preferred consistent query answers.     

The integrity constraints for similarity-based fuzzy relational databases

This paper first introduces a new definition for the conformance of tuples existing in a similarity-based fuzzy database relation. Then the formal definitions of fuzzy functional and multivalued dependencies are given on the basis of the conformance values presented here. These dependencies are defined to represent relationships between domains of the same relation that exist. The definitions of the fuzzy dependencies presented in this study allow a sound and complete set of inference rules. In this paper, we include examples to demonstrate how the integrity constraints imposed by these dependencies are enforced whenever a tuple is to be inserted or to be modified in a fuzzy database relation. © 1998 John Wiley & Sons, Inc.     

Fuzzy relations and fuzzy relational databases

This paper deals with the connections existing between fuzzy set theory and fuzzy relational databases. Our new result dealing with fuzzy relations is how to calculate the greatest lower bound (glb) of two similarity relations. Our main contributions in fuzzy relational databases are establishing from fuzzy set theory what a fuzzy relational database should be (the result is both surprising and elegant), and making fuzzy relational databases even more robust.Our work in fuzzy relations and in fuzzy databases had led us into other interesting problems—two of which we mention in this paper. The first is primarily mathematical, and the second provides yet another connection between fuzzy set theory and artificial intelligence. In understanding similarity relations in terms of other fuzzy relations and in making fuzzy databases more robust, we work with closure and interior operators; we present some important properties of these operators. In establishing the connection between fuzzy set theory and artificial intelligence, we show that an abstraction on a set is in fact a partition on the set; that is, an abstraction defines an equivalence relation on the underlying set.     

A new definition of fuzzy functional dependency in fuzzy relational databases

The need to incorporate and treat information given in fuzzy terms in Relational Databases has concentrated a great effort in the last years. This article focuses on the treatment of functional dependencies (f.d.) between attributes of a relation scheme. We review other approaches to this problem and present some of its missfunctions concerning intuitive properties a fuzzy extension of f.d. should verify. Then we introduce a fuzzy extension of this concept to overcome the previous anomalous behaviors and study its properties. of primary interest is the completeness of our fuzzy version of Armstrong axioms in order to derive all the fuzzy functional dependencies logically implied by a set of f.f.d. just using these axioms. © 1994 John Wiley & Sons, Inc.     

A logic approach to fuzzy relational databases

A new definition of Fuzzy Relational Database is given by using logical concepts. With this definition it is possible to consider several kinds of fuzziness for the database attributes. A Domain Calculus-based query language is also established for the model. It allows us to formulate several types of queries with different lack of precision levels. © 1994 John Wiley & Sons, Inc.     

关系数据库中的模糊关联规则挖掘算法研究

关联是数据挖掘领域的一个重要研究课题。对模糊关联规则挖掘进行了研究,针对普通关联规则不能精确表达数据库中模糊信息关联性的问题,提出了一种新的模糊关联规则挖掘算法FARM_New,结果表明算法是有效的,提高了模糊挖掘的速度。     

Storing and querying fuzzy XML data in relational databases

Information imprecision and uncertainty exist in many real-world applications and for this reason fuzzy data management has been extensively investigated in various database management systems. Currently, introducing native support for XML data in relational database management systems (RDBMs) has attracted considerable interest with a view to leveraging the powerful and reliable data management services provided by RDBMs. Although there is a rich literature on XML-to-relational storage, none of the existing solutions satisfactorily addresses the problem of storing fuzzy XML data in RDBMs. In this paper, we study the methodology of storing and querying fuzzy XML data in relational databases. In particular, we present an edge-based approach to shred fuzzy XML data into relational data. The unique feature of our approach is that no schema information is required for our data storage. On this basis, we present a generic approach to translate path expression queries into SQL for processing XML queries.     

Algebraic identities and query optimization in a parametric modelfor relational temporal databases

This paper presents algebraic identities and algebraic query optimization for a parametric model for temporal databases. The parametric model has several features not present in the classical model. In this model, a key is explicitly designated with a relation, and an operator is available to change the key. The algebra for the parametric model is three-sorted; it includes 1) relational expressions that evaluate to relations, 2) domain expressions that evaluate to time domains, and 3) Boolean expressions that evaluate to TRUE or FALSE. The identities in the parametric model are classified as weak identities and strong identities. Weak identities in this model are largely counterparts of the identities in classical relational databases. Rather than establishing weak identities from scratch, a meta inference mechanism, introduced in the paper, allows weak identities to be induced from their respective classical counterpart. On the other hand, the strong identities will be established from scratch. An algorithm is presented for algebraic optimization to transform a query to an equivalent query that will execute more efficiently     

Fuzzy identification in fuzzy databases: The nuanced relational division

In the present article we review the main research works in fuzzy databases; propose an extension of relation division operator to fuzzy databases; provide a model for fuzzy information and resolve the identification problem in fuzzy databases. For this, three notions are relevant: (a) the concept of nuanced information for representing fuzzy values and the associated nuance, (b) the nuanced division operator, (c) the possibility of weighting attributes in order to express data and query pertinence and trust. We then show how to resolve the problem of fuzzy identification with the nuanced division operator. © 1994 John Wiley & Sons, Inc.     

Polaris: a system for query, analysis, and visualization ofmultidimensional relational databases

In the last several years, large multidimensional databases have become common in a variety of applications, such as data warehousing and scientific computing. Analysis and exploration tasks place significant demands on the interfaces to these databases. Because of the size of the data sets, dense graphical representations are more effective for exploration than spreadsheets and charts. Furthermore, because of the exploratory nature of the analysis, it must be possible for the analysts to change visualizations rapidly as they pursue a cycle involving first hypothesis and then experimentation. In this paper, we present Polaris, an interface for exploring large multidimensional databases that extends the well-known pivot table interface. The novel features of Polaris include an interface for constructing visual specifications of table-based graphical displays and the ability to generate a precise set of relational queries from the visual specifications. The visual specifications can be rapidly and incrementally developed, giving the analyst visual feedback as he constructs complex queries and visualizations     

Schema mapping and query translation in heterogeneous P2P XML databases

Peers in a peer-to-peer data management system often have heterogeneous schemas and no mediated global schema. To translate queries across peers, we assume each peer provides correspondences between its schema and a small number of other peer schemas. We focus on query reformulation in the presence of heterogeneous XML schemas, including data–metadata conflicts. We develop an algorithm for inferring precise mapping rules from informal schema correspondences. We define the semantics of query answering in this setting and develop query translation algorithm. Our translation handles an expressive fragment of XQuery and works both along and against the direction of mapping rules. We describe the HePToX heterogeneous P2P XML data management system which incorporates our results. We report the results of extensive experiments on HePToX on both synthetic and real datasets. We demonstrate our system utility and scalability on different P2P distributions.     

Logic-based query optimization for object databases

We present a technique for transferring query optimization techniques, developed for relational databases, into object databases. We demonstrate this technique for ODMG database schemas defined in ODL and object queries expressed in OQL. The object schema is represented using a logical representation (Datalog). Semantic knowledge about the object data model, e.g., class hierarchy information, relationship between objects, etc., as well as semantic knowledge about a particular schema and application domain are expressed as integrity constraints. An OQL object query is represented as a logic query and query optimization is performed in the Datalog representation. We obtain equivalent (optimized) logic queries, and subsequently obtain equivalent (optimized) OQL queries for each equivalent logic query. We present one optimization technique for semantic query optimization (SQO) based on the residue technique of U. Charavarthy et al. (1990; 1986; 1988). We show that our technique generalizes previous research on SQO for object databases. We handle a large class of OQL queries, including queries with constructors and methods. We demonstrate how SQO can be used to eliminate queries which contain contradictions and simplify queries, e.g., by eliminating joins, or by reducing the access scope for evaluating a query to some specific subclass(es). We also demonstrate how the definition of a method or integrity constraints describing the method, can be used in optimizing a query with a method     

A query algebra for program databases

Querying source code is an essential aspect of a variety of software engineering tasks such as program understanding, reverse engineering, program structure analysis and program flow analysis. In this paper, we present and demonstrate the use of an algebraic source code query technique that blends expressive power with query compactness. The query framework of Source Code Algebra (SCA) permits users to express complex source code queries and views as algebraic expressions. Queries are expressed on an extensible, object-oriented database that stores program source code. The SCA algebraic approach offers multiple benefits such as an applicative query language, high expressive power, seamless handling of structural and flow information, clean formalism and potential for query optimization. We present a case study where SCA expressions are used to query a program in terms of program organization, resource flow, control flow, metrics and syntactic structure. Our experience with an SCA-based prototype query processor indicates that an algebraic approach to source code queries combines the benefits of expressive power and compact query formulation     

Time-by-example query language for historical databases

The authors propose a graphical query language, Time-by-Example (TBE), which has suitable constructs for interacting with historical relational databases in a natural way. TBE is user-friendly. It follows the graphical, two-dimensional approach of such previous languages as Query-by-Example (QBE), Aggregation-by-Example (ABE), and Summary-Table-by-Example (STBE). TBE also uses the hierarchical window (subquery) concept of ABE and STBE. TBE manipulates triple-valued (set-triple-valued) attributes and historical relations. Set-theoretic expressions are followed to deal with time intervals. The BNF specification for TBE is given     

XML数据库和关系数据库之比较

XML已经成为数据表示和交换的数据格式标准。随着大量XML文档的出现,应用数据库技术实现对XML数据的管理引起了越来越多研究者的兴趣。作为研究XML数据库技术的一个开始点,通过与关系数据库比较,可以深刻理解XML数据库与关系数据库的异同,进而为解决XML数据库所面临的问题,如为数据冗余控制、并发访问控制等提供必要的基础。两种数据库的比较是从数据模型、查询路径、完整性约束和规范化5个方面进行的,由于数据模型是数据库的基石,二者的数据模型从构造机制、名字的惟一性、空值、实体标识、实体问关系、文档顺序、数据结构的规则性、递归、数据自描述性等9个方面进行了详细讨论。