In this paper we present DDDiver, a tool for the interactive visualization and editing of object-oriented databases. It was developed to visualize and manipulate large loosely-structured data sets with multiple relati...
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(纸本)3211836748
In this paper we present DDDiver, a tool for the interactive visualization and editing of object-oriented databases. It was developed to visualize and manipulate large loosely-structured data sets with multiple relation types. This makes the tool especially useful in application areas that involve product data models, design information systems, and semantic networks. DDDiver can visualize such relational data sets in a 3d graph. The layout mechanism used for the graph is not based on a deterministic mathematical algorithm, but on the distinction between a number of relation kinds, and on user interaction. The intuitiveness and quickness of the visualization tool was further improved by adding animated visual feedback effects.
The paper attempts theoretically to clarify the interrelation between various levels of descriptions used in the modelling and the programming of information systems. We suggest an analysis where we characterise the d...
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This article introduces a segmentation method to auto- matically extract object parts from a reduced set of images. Given a database of objects and dividing all of them using local color histograms, we obtain an objec...
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Data mining is the discovery of knowledge and useful information from the large amounts of data stored in databases. With the increasing popularity of object-oriented database systems in advanced database applications...
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Data mining is the discovery of knowledge and useful information from the large amounts of data stored in databases. With the increasing popularity of object-oriented database systems in advanced database applications, it is important to study the data mining methods for object-oriented databases because mining knowledge from such databases may improve understanding, organization, and utilization of the data stored there. In this paper, issues on generalization-based data mining in object-oriented databases are investigated in three aspects: (1) generalization of complex objects, (2) class-based generalization, and (3) extraction of different kinds of rules. An object cube model is proposed for class-based generalization, on-line analytical processing, and data mining. The study shows that (i) a set of sophisticated generalization operators can be constructed for generalization of complex data objects, (ii) a dimension-based class generalization mechanism can be developed for object cube construction, and (iii) sophisticated rule formation methods can be developed for extraction of different kinds of knowledge from data, including characteristic rules, discriminant rules, association rules, and classification rules. Furthermore, the application of such discovered knowledge may substantially enhance the power and flexibility of browsing databases, organizing databases and querying data and knowledge in object-oriented databases.
Much work has been accomplished in the past on the subject of parallel query processing and optimization in parallel relational database systems;however, little work on the same subject has been done in parallel objec...
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Much work has been accomplished in the past on the subject of parallel query processing and optimization in parallel relational database systems;however, little work on the same subject has been done in parallel object-oriented database systems. Since the object-oriented view of a database and its processing are quite different from those of a relational system, it can be expected that techniques of parallel query processing and optimization for the latter can be different from the former. In this paper, we present a general framework for parallel object-oriented database systems and several implemented query processing and optimization strategies together with some performance evaluation results. In this work, multiwavefront algorithms are used in query processing to allow a higher degree of parallelism than the traditional tree-based query processing. Four optimization strategies, which are designed specifically for the multiwavefront algorithms and for the optimization of single as well as multiple queries, are introduced. The query processing algorithms and optimization strategies have been implemented on a parallel computer, nCUBE2;and the results of a performance evaluation are presented in this paper. The main emphases and the intended contributions of this paper are (1) data partitioning, query processing and optimization strategies suitable for parallel OODBMSs, (2) the implementation of the multiwavefront algorithms and optimization strategies, and (3) the performance evaluation results.
objects in a database are interrelated. When an update operation is applied to an object, it may also impact on its related objects, depending on the semantics of their relationships. Current OODBMSs provide no suppor...
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objects in a database are interrelated. When an update operation is applied to an object, it may also impact on its related objects, depending on the semantics of their relationships. Current OODBMSs provide no support for update propagation but hard-coding. In this paper, we study update propagation support for generic update operations in object-oriented databases. We take a declarative approach, specifying propagation policies for each identified reference attribute in classes of an object-oriented database schema. Propagation policies for generic update propagation are well defined. However, we also discover that potential conflicts among propagation policies may occur if the policies can be arbitrarily specified by a designer. Therefore, we promote the update propagation problem to a higher level, investigating possible dependencies between objects. As such, the designer only needs to specify the dependency property for each reference attribute. Propagation policies are predefined for each type of dependency. By introducing some restrictions on an object-oriented database schema, conflict-free propagation policies can be achieved. Implementation issues for update propagation support in object-oriented database systems are also addressed.
The focus of this article is the transformation of conceptual data models (such as ER, NIAM and PSM) to object-oriented databases. This transformation is captured within the framework of a two-level architecture. Conc...
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The focus of this article is the transformation of conceptual data models (such as ER, NIAM and PSM) to object-oriented databases. This transformation is captured within the framework of a two-level architecture. Conceptual models are first mapped to abstract intermediate specifications, which are then transformed to database schemas in a given object-oriented database environment. This enables us to treat different target systems in a uniform way. As final implementation environments, we consider object-oriented as well as object-relational DBMSs, including the SQL3 and ODMG-93 standards. We do not reveal the specific details of these standards. Rather, we use intermediate representations expressed in F-logic, a logic-based abstract specification language for object-oriented systems. Several transformation alternatives are discussed in a formal context, resulting in a collection of design options. (C) 1998 Elsevier Science B.V.
Integration of data from autonomous, distributed and heterogeneous data sources poses several technical challenges. This paper overviews the data integration system AMOS II based on the wrapper-mediator approach. AMOS...
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Integration of data from autonomous, distributed and heterogeneous data sources poses several technical challenges. This paper overviews the data integration system AMOS II based on the wrapper-mediator approach. AMOS II consists of. (i) a mediator database engine that can process and execute queries over data stored locally and in several external data sources, and (ii) object-oriented (OO) multi-database views for reconciliation of data and schema heterogeneities among sources with various capabilities. The data stored in different types of data sources is translated and integrated using OO mediation primitives, providing the user with a consistent view of the data in all the sources. Through its multi-database facilities many distributed AMOS II systems can interoperate in a federation. Since most data reside in the data sources, and to achieve high performance, the core of the system is a main-memory DBMS having a storage manager, query optimizer, transactions, client-server interface, disk backup, etc. The AMOS II data manager is optimized for main-memory access and is extensible so that new data types and query operators can be added or implemented in some external programming language. The extensibility is essential for providing seamless access to a variety of data sources. Copyright (C) 2001 John Wiley & Sons, Ltd.
The need for incremental algorithms for evaluating database queries is well known, but constructing algorithms that work on object-oriented databases (OODBs) has been difficult. The reason is that OODB query languages...
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The need for incremental algorithms for evaluating database queries is well known, but constructing algorithms that work on object-oriented databases (OODBs) has been difficult. The reason is that OODB query languages involve complex data types including composite objects and nested collections. As a result, existing algorithms have limitations in that the kinds of database updates are restricted, the operations found in many query languages are not supported, or the algorithms axe too complex to be described precisely. We present an incremental computation algorithm that can handle any kind of database updates, can accept any expressions in complex query languages such as OQL, and can be described precisely. By translating primitive values and records into collections, we can reduce all query expressions into ones composed of only one kind of operation, namely comprehension. This makes the problems with incremental computation less complicated and thus allows us to describe the algorithm precisely. Our incremental algorithm consists of two parts: one is to maintain the consistency in each comprehension occurrence and the other is to update the value of an entire expression. The algorithm is so flexible that we can use strict updates, lazy updates, and their combinations. By comparing the performance of applications built with our mechanism and that of equivalent hand written update programs, we show that our incremental algorithm can be implemented efficiently.
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