Showing papers on "Graph database published in 1995"

Design and evaluation of algorithms for image retrieval by spatial similarity

Abstract: Similarity-based retrieval of images is an important task in many image database applications. A major class of users' requests requires retrieving those images in the database that are spatially similar to the query image. We propose an algorithm for computing the spatial similarity between two symbolic images. A symbolic image is a logical representation of the original image where the image objects are uniquely labeled with symbolic names. Spatial relationships in a symbolic image are represented as edges in a weighted graph referred to as spatial-orientation graph. Spatial similarity is then quantified in terms of the number of, as well as the extent to which, the edges of the spatial-orientation graph of the database image conform to the corresponding edges of the spatial-orientation graph of the query image.The proposed algorithm is robust in the sense that it can deal with translation, scale, and rotational variances in images. The algorithm has quadratic time complexity in terms of the total number of objects in both the database and query images. We also introduce the idea of quantifying a system's retrieval quality by having an expert specify the expected rank ordering with respect to each query for a set of test queries. This enables us to assess the quality of algorithms comprehensively for retrieval in image databases. The characteristics of the proposed algorithm are compared with those of the previously available algorithms using a testbed of images. The comparison demonstrated that our algorithm is not only more efficient but also provides a rank ordering of images that consistently matches with the expert's expected rank ordering.

Graph Grammar Engineering with PROGRES

Abstract: Graph-like data structures and rule-based systems play an important role within many branches of computer science. Nevertheless, their symbiosis in the form of graph rewriting systems or graph grammars are not yet popular among software engineers. This is a consequence of the fact that graph grammar tools were not available until recently and of the lack of knowledge about how to use graph grammars for software development purposes. “Graph grammar engineering” is a first attempt to establish a new graph and rule centered methodology for the development of information system components. Having its roots in the late 80's it gradually evolved from a “paper and pencil” specification formalism to a tool-assisted specification and rapid prototyping approach.

A theory of translation from relational queries to hierarchical queries

Abstract: In a heterogeneous database system, a query for one type of database system (i.e., a source query) may have to be translated to an equivalent query (or queries) for execution in a different type of database system (i.e., a target query). Usually, for a given source query, there is more than one possible target query translation. Some of them can be executed more efficiently than others by the receiving database system. Developing a translation procedure for each type of database system is time-consuming and expensive. We abstract a generic hierarchical database system (GHDBS) which has properties common to database systems whose schema contains hierarchical structures (e.g., System 2000, IMS, and some object-oriented database systems). We develop principles of query translation with GHDBS as the receiving database system. Translation into any specific system can be accomplished by a translation into the general system with refinements to reflect the characteristics of the specific system. We develop rules that guarantee correctness of the target queries, where correctness means that the target query is equivalent to the source query. We also provide rules that can guarantee a minimum number of target queries in cases when one source query needs to be translated to multiple target queries. Since the minimum number of target queries implies the minimum number of times the underlying system is invoked, efficiency is taken into consideration. >

Searching for pharmacophoric patterns in databases of three-dimensional chemical structures.

Abstract: This paper provides an overview of the research that has been carried out in Sheffield over the last decade into searching techniques for databases of three-dimensional (3D) chemical structures. A 3D structure or query pattern is represented by a labelled graph, in which the nodes and the edges of the graph are used to represent atoms and the associated inter-atomic distances, respectively. The presence of a pharmacophore in each of the structures in a database can then be tested by means of a subgraph isomorphism algorithm, the computational requirements of which are minimized by the use of an initial screening procedure that eliminates the majority of the structures from the subgraph-isomorphism search. Analogous graph-based representation and searching methods can also be used with flexible 3D structures: in this case, the edges of the graphs represent inter-atomic distance ranges and a final conformational search needs to be carried out for those molecules that match the query pharmacophore in the subgraph-isomorphism search. The paper also reviews related work on the automatic identification of pharmacophoric patterns and on 3D similarity searching.

Dynamic database structuring method and apparatus, and database clustering method and apparatus

Abstract: A dynamic database structuring method includes the steps of (a) clustering transition probabilities among transactions by on-line, (b) forming a hyper graph representing the transition probabilities of the transactions clustered in the step (a) using weighting, (c) partitioning the hyper graph to obtain clustering information related to objects or records to be stored in a storage, and (d) reorganizing a database by rearranging data in the storage by on-line using the clustering information obtained in the step (c), thereby restructuring the database dynamically.

Graph database systems

Abstract: We have investigated using graphs as the foundation for database systems by developing a graph-based DBMS. We have demonstrated that: 1. Graph-based representations are useful for representing genome data. 2. A graph data model tailored to the requirements of genome data can be used as the basis of a database management system. 3. A graph database management system is a viable technology for storing genome data. We have found that graph-based technologies are useful in multiple aspects of database development, and we plan to expand on the capabilities of graphs for developing genome databases. >

A graph-theoretic data model for genome mapping databases

Abstract: Graphs are a natural foundation for genome map databases. Mapping and other genomic data can be clearly represented by graphs, and graphs can be stored in a database. Graphs are defined as a collection of nodes and arcs and can represent genomic objects and relationships between them. Mapping databases are needed to store the rapidly growing amount of mapping data. These databases must store the information contained in both published maps and laboratory notebooks. We describe a graph database which can store mapping data directly as graphs and formalize it as a graph-theoretic data model. >

Storage of a graph

Abstract: The invention relates to a method to store a graph G in a memory of a computer system by a number of depth-first and breadth-first searches in different directions. The entire topological information contained in the graph is mapped into the memory. At the same time redundant information is eliminated.

Method for learning data processing rules from graph information

Abstract: A learning method for performing a method of inductively learning rules from machine data, and a method for analyzing an inference process to learn rules useful for increasing efficiency by a common program are provided. Data desired to be classified is converted into a graph and is then input. The course of process by a computer is also converted into a graph and is then input. Then, patterns appearing in the input graph are extracted and patterns having a good evaluation result are output. The patterns are converted into rules for classification and rules for high-speed operation in accordance with a kind of the input graph, and are output.

Accessing a Relational Database through an Object-Oriented Database Interface

Abstract: Object-oriented database systems (ODBs) are designed for use in applications characterized by complex data models, clean integration with the host programming language, and a need for extremely fast creation, traversal, and update of networks of objects These applications are typically written in C or C++, and the problem of how to store the networks of objects, and update them atomically has been difficult in practice Relational database systems (RDBs) tend to be a poor fit for these applications because they are designed for applications with different performance requirements ODBs are designed to meet these requirements and have proven more successful in pioviding”persistence for applications such as ECAD and MCAD’ Interest in ODBs has-spread be$ond the CAD communities, to areas such as finance and telecommunications These applications have many similarities to CAD applications For example, in financial applications, the data structures describing a mutual fund’s portfolio can be quite complex, applications are written in C or C++, and fast traversal of the data structures is important These application areas often have an additional requirement the need to make use of “legacy” data stored in relational database systems (RDBs) For years, the developers of these applications have worked in non-object-oriented languages; and have had to deal with the problem of turning tuple streams into the complex data structures manipulated by their applications Now, the developers who have started using object-oriented languages and database systems would like to continue the transition by insulating themselves from the relational model and SQL

Graph-Theoretical Methods to Construct Entity-Relationship Databases

Abstract: Within the recent years, the entity-relationship approach has become one of the most popular methods in high-level database design. In this approach data are modelled as entity and relationship types. Usually relationship types come along with certain restrictions that influence the structure of databases. Cardinality constraints are the most commonly used class of constraints used to model such restrictions. Database instances satisfying given cardinality constraints are said to be valid. The aim of this paper is to show how to use methods from graph theory to determine the class cardinalities of entity and relationship types in valid databases. We develop algorithms for this purpose and a number of variations of the problem, namely to construct databases of minimum size and linear ternary databases.

The GraphDB Algebra: Specification of Advanced Data Models with Second-Order Signature

Abstract: A framework using so called second-order signature for the specification of database models has been presented in earlier work. The goal of this approach is to provide generic tools for the implementation of database systems, in particular for parsing and rule-based optimization and for execution of query plans, that can be used with widely varying data models and query languages. In this paper we apply this specification technique to the graph based data model GraphDB. We develop an algebraic description for the querying facilities of GraphDB and use second-order signature to specify the GraphDB data model and its algebra.

Application of object-oriented technology for integrating heterogeneous database systems

Abstract: This paper describes the current challenges on the interoperability of heterogeneous database management systems and then focusses on the role of the objectoriented approach to facilitate the interconnection of multiple database systems.

Semantic Optimization of Biomolecular Queries in Object-oriented Database Systems

Abstract: Research efforts in molecular biology have led to an explosion both in quantity and quality ofbiomolecular data. In particular databases that integrate data from many different, heterogeneousinformation resources lead to complex database schemas and large databases. In order to support theuser in creatively exploiting these information resources, flexible and efficient retrieval capabilities areneeded.We sketch in this paper our approach to optimization of declarative queries in object-oriented databases,that allows to exploit the specific semantic characteristic of datatypes occurring in scientific applicationslike molecular biology. These processing capabilities are used within the German national joint projectRELIWE (RELIWE is a research consortium in which EMBL Heidelberg , GMD-IPSI and GMD-SCAIparticipate as research institutions, and BASF, Ludwigshafen and E. Merck, Darmstadt participate asindustrial partners; the project is funded by the German "Bundesministerium fuer Bildung undWissenschaft" BMBW, grant number 01IB302E.). In RELIWE’s subproject Docking-D an integratedprotein/ligand database covering many datasets, that are relevant for drug design [1], including PDB ,Swissprot, PIR , DSSP, HSSP and PMD, has been developed on top of GMD-IPSI’s object-orienteddatabase system VODAK [16]. Dedicated indexing mechanisms and algorithms are integrated with thedatabase system in order to provide the user with powerful and efficient access mechanisms. The datahas been integrated physically for efficiency reasons, however, conceptually also the virtual integrationof databases is feasible and will be used in the future for integrating further information resources, likeMedline.

A Temporal Logic Based Approach for Querying Lists, Trees, and DAGs in Databases

Abstract: Although lists, trees, and directed acyclic graphs (dags) are of fundamental interest in computer science, they have scarcely been noticed as data types by existing database systems and database models. In this article I present query language concepts for (object-oriented) database systems offering such non-traditional data resp. object types. For the main task of such a query language, namely the specification of predicates on instances of these types, a temporal logic approach is used. For this, an existing timely oriented approach for querying lists is extended by incorporating concepts from the area of branching-time logics. This article mainly presents the logic concepts of the query language and an implementation of these concepts in an object base systems for discrete structures.

FuzzyBase: A Fuzzy Logic Aid for Relational Database Queries

Abstract: This paper presents a similarity query generator for DBMSs. A user query which turns out to be too restrictive and returns an empty set of rows is relaxed and transformed into a similar one: the resulting set of tuples will resemble, at some degree, the set defined by the original query. The relaxing activity is based on fuzzy logic and the system provides a user interface to express the query, to obtain suggestions on possible search values and to validate, on the basis of semantic integrity rules, the expressed conditions.

Image Retrieval Method based on Graph Matching of Structured Information.

Abstract: An image retrieval system providing effective access to desired data in an image database has been studied. Since images are more ambiguous than language, image retrieval that uses only a keyword as a retrieval key is not enough. In this paper, we propose an image retriaval method that uses a rough sketch as the retrieval key. An image in a database system is divided into segments and is described by color, position, size, shape, and geographical relation of each area. These structural features are represented by attributed relational graphs. Similarity is measured by graph matching between stored graphs and a graph derived from a rough sketch.

Path view algorithm for transportation networks : dynamic reordering approach

Abstract: Efficient path computation, necessary for route guidance, is one of the key requirements for Intelligent Transportation Systems (ITS). This paper presents a new path view algorithm that computes the materialized path view for an ITS graph database in order to efficiently support a large number of path queries.

Parallel Processing of Image Database Queries

Abstract: This paper treats data structures for image representation and parallel algorithms for operations associated with databases of images. In our approach, images are converted from input pixel form to linear quadtrees that allow efficient storage of image data and that are suitable for a large number of operations. We have designed and implemented algorithms for set operations — union, intersection, difference, and for relational database operations — selection, projection and join. These operations are essential for data retrieval in spatial database queries. All the algorithms mentioned above were developed on MasPar SIMD (Single Instruction Multiple Data) parallel computer equipped with 1024 processors.