Query Languages for Multimedia Search

Data mining is the discovery of knowledge and useful information from the large amounts of data stored in databases. The emerging data mining tools and systems lead to the demand of a powerful data mining query language. The concepts of such a language for relational databases are discussed before. With the increasing popularity of object-oriented databases, it is important to design a data mining query language for such databases. The main objective of this paper is to propose an Object Data Mining Query Language (ODMQL) for object-oriented databases as an extension to the Object Query Language (OQL) proposed by the Object Data Management Group (ODMG) as a standard query language for object-oriented databases. The proposed language is implemented as a feature of an experimental object-oriented database management system that is developed as a testbed for research issues of object-oriented databases.

In this paper we introduce DOODLE, a new visual and declarative language for object-oriented databases. The main principle behind the language is that it is possible to display and query the database with arbitrary pictures . We allow the user to tailor the display of the data to suit the application at hand or her preferences. We want the user-defined visualizations to be stored in the database, and the language to express all kinds of visual manipulations. For extendibility reasons, the language is object-oriented. The semantics of the language is given by a well-known deductive query language for object-oriented databases. We hope that the formal basis of our language will contribute to the theoretical study of database visualizations and visual query languages, a subject that we believe is of great interest, but largely left unexplored.

We define a graph based visual query language for object databases, called QUIVER. Most graph based query languages proposed in the literature view queries either as constraint (pattern) graphs or as data flow graphs. QUIVER, however allows constraints and data flow to be combined in queries. This combination of constraints and data flow is motivated by the need to support comprehensive object models, such as that proposed by the Object Data Management Group (ODMG). QUIVER supports all ODMG object model constructs, including computational constructs such as operations (methods). In addition, QUIVER supports computational query constructs such as subqueries and (aggregate) functions.

Query languages for graph databases started to be investigated some 25 years ago. With much current data, such as linked data on the Web and social network data, being graph-structured, there has been a recent resurgence in interest in graph query languages. We provide a brief survey of many of the graph query languages that have been proposed, focussing on the core functionality provided in these languages. We also consider issues such as expressive power and the computational complexity of query evaluation.

Path expressions have been accepted for concisely manipulating the nested structures in complex object-oriented query expressions. However, previous visual query languages hardly represent such query expressions in a concise and intuitive way partly due to improper visual representation of path expressions and partly due to lack of well-defined system and semantics of languages. In this paper, we present visual modeling of path expressions in a visual object-oriented database query language called Visual Object-Oriented Query Language (VOQL) which has excellent expressive pourer for sets, simple and intuitive syntax, and well-defined semantics. This is enabled by explicitly specifying the semantics of multi-valued path expressions based on the visual notation capable of representing set relationships in addition to functional relationships. The basic visual constructs called blobs and nested blobs denote sets of objects that path expressions represent while the constructs called binding edges and flattening edges visually simulate the notions of variable binding and dot functions in path expressions respectively. Based on the constructs, the grammar of VOQL defines the syntactic components while the semantics of query expressions are provided by syntax-directed translation to the counterparts in the extended relational calculus. Also, the visual constructs allow modeling of restricted universal quantification with a visual scoping box and effectively represent nested quantification and recursive queries without semantic ambiguities.

Several query languages have been proposed in which users graphically manipulate Entity-Relationship (ER) diagrams to formulate queries. In this paper we present a method of implementing an ER query and update language as an interface for a relational Database Management System. The approach is based on interactive manipulation of ER database schemas and generation of SQL expressions for an underlying relational database. The graphical query and update formulation process is formally defined. We assume that the information reflecting the current state of the query and update formulation process is maintained in a formal model. The model described in other publications is significantly modified and extended. The information included in the extended model allows an ER diagram corresponding to the current state of the query to be displayed on the terminal screen. It is also used to generate an equivalent SQL expression for a relational database. The integrity constraints for the formal model are specified.

In this paper, we discuss some design principles that will aid in the design and querying of multimedia databases. We use an object-relational data model and argue that multimedia objects should normally have a special attribute called ‘core’ which stores the real object itself in contrast to the abstraction which is reflected in the rest of the attributes. We present an extension to the ER Diagram that takes advantage of the ‘core’ notion to facilitate design of multimedia databases. We discuss some desirable features in a query language for multimedia databases: simplifications like the use of path expressions and implicit use of functions (methods) as attributes, and explicit specification of the display layout and format either at the data definition level or query specification level. To materialize this last feature, we propose a display specification extension to SQL (SQL+D) that we have implemented.

The study of query languages for spatial databases is an active research area. This paper describes a new spatial query language that uses a visual grammar to express topological relationships. It is supplemented by text and icons to handle other spatial and non-spatial queries. A graphical user interface is also developed to provide an interactive environment for composing the iconic query command. To test the language, the interface is implemented on a SUN 4 Workstation and linked to Ingres, a relational DBMS. Preliminary tests show that the iconic query language is more convenient for expressing spatial concepts than conventional textual languages. This is due mainly to the two-dimensionality of iconic languages in contrast with the linear nature of conventional languages.

We study adding aggregate operators, such as summing up elements of a column of a relation, to logics with counting mechanisms. The primary motivation comes from database applications, where aggregate operators are present in all real life query languages. Unlike other features of query languages, aggregates are not adequately captured by the existing logical formalisms. Consequently, all previous approaches to analyzing the expressive power of aggregation were only capable of producing partial results, depending on the allowed class of aggregate and arithmetic operations. We consider a powerful counting logic, and extend it with the set of all aggregate operators. We show that the resulting logic satisfies analogs of Hanf's and Gaifman's theorems, meaning that it can only express local properties. We consider a database query language that expresses all the standard aggregates found in commercial query languages, and show how it can be translated into the aggregate logic, thereby providing a number of expressivity bounds, that do not depend on a particular class of arithmetic functions, and that subsume all those previously known. We consider a restricted aggregate logic that gives us a tighter capture of database languages, end also use it to show that some questions on expressivity of aggregation cannot be answered without resolving some deep problems in complexity theory.

Graph analytics is becoming increasingly popular, driving many important business applications from social network analysis to machine learning. Since most graph data is collected in a relational database, it seems natural to attempt to perform graph analytics within the relational environment. However, SQL, the query language for relational databases, makes it difficult to express graph analytics operations. This is because SQL requires programmers to think in terms of tables and joins, rather than the more natural representation of graphs as collections of nodes and edges. As a result, even relatively simple graph operations can require very complex SQL queries. In this paper, we present GRAPHiQL, an intuitive query language for graph analytics, which allows developers to reason in terms of nodes and edges. GRAPHiQL provides key graph constructs such as looping, recursion, and neighborhood operations. At runtime, GRAPHiQL compiles graph programs into efficient SQL queries that can run on any relational database. We demonstrate the applicability of GRAPHiQL on several applications and compare the performance of GRAPHiQL queries with those of Apache Giraph (a popular ‘vertex centric’ graph programming language).

A Fuzzy Query Language (FQL) for relational databases is proposed. FQL, developed as an extension of relational domain calculus, has sufficient capabilities to express all five types of fuzzy statements distinguished and represented in a meaning representation language PRUF by 7aieh. The main idea for developing FQL lies in a method that harmoniously integrates relational domain calculus and PRUF, together with a natural determination method of matching degrees of domain values in relational databases against FQL queries. Effects of FQL are twofold. One is practical. We expect that FQL will add a human-oriented interface to currently widespread relational databases all over the world that have already stored a vast amount of useful information. In addition, fuzzy expert systems currently under development can be designed to support FQL so that they can make use of fact data stored in some relational database in their processing. The other but principal effect is theoretical. FQL provides a theoretical framework that can play a kernel role in integrating many previous-and-future fuzzy extensions of relational database query languages systematically into a unified fuzzy query language.KeywordsRelational databasesquery languagefuzzy propositionsfuzzy well-formed formulasrelational domain calculusmatching degrees

With the prevalence of graph data in a variety of domains, there is an increasing need for a language to query and manipulate graphs with heterogeneous attributes and structures. We present a graph query language (GraphQL) that supports bulk operations on graphs with arbitrary structures and annotated at- tributes. In this language, graphs are the basic unit of information and each query manipulates one or more collections of graphs at a time. The core of GraphQL is a graph algebra extended from the relational algebra in which the selection operator is generalized to graph pattern matching and a composition operator is introduced for rewriting matched graphs. Then, we investigate access methods of the selection operator. Pattern matching over large graphs is challenging due to the NP-completeness of subgraph isomorphism. We address this by a combination of techniques: use of neighborhood subgraphs and pro- files, joint reduction of the search space, and optimization of the search order. Experimental results on real and synthetic large graphs demonstrate that graph specific optimizations outperform an SQL-based implementation by orders of magnitude.

Query languages for relational databases have received considerable attention. In 1972 Codd [Cod72] showed that two natural mathematical languages for queries—one algebraic and the other a version of first order predicate calculus—had identical powers of expressibility. Query languages which are as expressive as Codd's Relational Calculus are sometimes called complete. This term is misleading, however, because many interesting queries are not expressible in “complete” languages.

On the expressiveness of linear-constraint query languages for spatial databases

Section 3.1 describes the relational data model, which is a particular data abstraction that uses relations or tables to represent the data in a database. Section 3.2 introduces the relational algebra query language, while Section 3.3 introduces the Structured Query Language (SQL) for relational databases. Finally, Section 3.4 discusses the evaluation of relational database queries.KeywordsRelational DatabaseQuery LanguageRelational AlgebraSocial Security NumberStructure Query LanguageThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.