Research into knowledge representation within the artificial intelligence (AI) community has led to the development of AI tools that use frames to structure knowledge. Concurrent research in databases has led to the d...
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Research into knowledge representation within the artificial intelligence (AI) community has led to the development of AI tools that use frames to structure knowledge. Concurrent research in databases has led to the development of semantic data models and object-oriented databases. These two types of system seem to have much in common - they are structurally object-oriented, support inheritance, and store programs with the objects to which they relate. What then are the differences between frame systems and object-oriented databases? The paper compares a frame system called CRL with an object-oriented database called ADAM to identify common ground and differences between the systems and the philosophies underlying them. What emerges from the comparison is that while the systems have many superficial similarities, the different rationales that led to their development have resulted in significant practical differences in certain fundamental constructs.
As applications have grown more sophisticated, they have placed greater demands on underlying database technology. In this paper we examine some of the shortcomings of conventional database technologies in the face of...
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The goal of the First ECOOP Workshop on object-oriented databases was to bring together researchers working in the field of object-oriented databases, to discuss the work which is going on. The aim of the workshop was...
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ISBN:
(纸本)354066954X
The goal of the First ECOOP Workshop on object-oriented databases was to bring together researchers working in the field of object-oriented databases, to discuss the work which is going on. The aim of the workshop was twofold: to discuss the current status of research in the field and to critically evaluate object-oriented database systems in terms of their current usage, of their successes and limitations, and their potential for new applications. The workshop thus consisted of a number of presentations of reviewed papers and of discussions on the topics mentioned above.
In the paper, the authors attempt to extend the query model of ORION. The extension is based on adding two new features. First, is to extend relational algebra operations and set-theoretic operations to the world of c...
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In the paper, the authors attempt to extend the query model of ORION. The extension is based on adding two new features. First, is to extend relational algebra operations and set-theoretic operations to the world of classes. Second, to allow new classes to be created as a result of applying these operations on classes along the lines of relational databases. The extended query model allows a query against multiple target classes, i.e., a query that corresponds to relational join and set operations. It also enables the authors to retrieve complex objects and extracts attributes from component-type hierarchy equivalent to relational select and project operations respectively.
This article investigates an extensible approach to processing temporal queries in the context of object-oriented databases. Within the uniform query processing framework, a strategy of decomposition is proposed for p...
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This article investigates an extensible approach to processing temporal queries in the context of object-oriented databases. Within the uniform query processing framework, a strategy of decomposition is proposed for processing temporal queries that involve paths based on the defined temporal object data model and query algebra. Algorithms for processing the decomposed query components have been implemented using stream processing techniques and are presented with cost analyses. Heuristics that optimize the temporal queries are also presented. Both cost analysis and simulations show that join time cost is linearly increased with the expansion in the number of time-epochs and that utilising the heuristics presented in this article can lead to a significant time cost saving. (C) 1999 Elsevier Science B.V. All rights reserved.
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.
In recent years, parallel processing and optimization algorithms for processing object-oriented databases have drawn a considerable amount of attention from the database research community. Two general types of algori...
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In recent years, parallel processing and optimization algorithms for processing object-oriented databases have drawn a considerable amount of attention from the database research community. Two general types of algorithms have been introduced: hybrid-hash pointer-based algorithms and multiwavefront algorithms. In this work, we quantitatively analyze the two algorithms and develop analytical formulas to capture the main performance features of these two approaches. We study their performance in three application environments: One is characterized by large databases having many object classes, each of which contains a large number of instances;the second one is characterized by large databases having many object classes, each of which contains a relatively small number of instances;and the third one is by large databases having object classes of varying sizes. A horizontal data partitioning strategy, in which each object class is partitioned into horizontal segments stored across all processors, is used in the first environment. A class-per-node assignment strategy, in which instances of each object class are stored in a single processor, is used in the second environment. In the third environment, object classes are partitioned horizontally and assigned to a varying number of processors depending on their different sizes. Our analytical results show that the multiwavefront algorithm has three distinguishing features which contribute to its better performance: 1) two-phase processing strategy, 2) vertical partitioning of horizontal segments, and 3) dynamic determination of "collision point" in multiwavefront propagations which results in an optimized query execution plan. We show that if these features are adopted by a hybrid-hash, pointer-based algorithm, its performance will be comparable with that of the multiwavefront algorithm because the difference in CPU time between them is negligible. The assumed computing environment is a network of workstations having a sha
Over the past decade, a large number of deductive object-oriented database languages have been proposed. The earliest of these languages had few object-oriented features, and more and more features have systematically...
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Over the past decade, a large number of deductive object-oriented database languages have been proposed. The earliest of these languages had few object-oriented features, and more and more features have systematically been incorporated in successive languages. However, a language with a clean logical semantics that naturally accounts for all the key object-oriented features, is still missing from the literature. This article takes us another step towards solving this problem. Two features that are currently missing are the encapsulation of rule-based methods in classes, and nonmonotonic structural and behavioral inheritance with overriding, conflict resolution and blocking. This article introduces the syntax of a language with these features. The language is restricted in the sense that we have omitted other object-oriented and deductive features that are now well understood, in order to make our contribution clearer. It then defines a class of databases, called well-defined databases, that have an intuitive meaning and develops a direct logical semantics for this class of databases. The semantics is based on the well-founded semantics from logic programming. The work presented in this article establishes a firm logical foundation for deductive object-oriented databases.
This paper presents a tunable two-dimensional class hierarchy indexing technique (2D-CHI) for object-oriented databases. We use a two-dimensional file organization as the index structure. 2D-CHI deals with the problem...
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This paper presents a tunable two-dimensional class hierarchy indexing technique (2D-CHI) for object-oriented databases. We use a two-dimensional file organization as the index structure. 2D-CHI deals with the problem of clustering objects in a two-dimensional domain space consisting of the key attribute domain and the class identifier domain. In conventional class indexing techniques using one-dimensional index structures such as the B+-tree, the clustering property is owned exclusively by one attribute. These indexing techniques do not handle the queries that address both the attribute keys and the class identifiers efficiently. 2D-CHI enhances query performance by adjusting the degree of clustering between the key value domain and the class identifier domain based on the precollected usage pattern. For performance evaluation, we first compare 2D-CHI with the conventional class indexing techniques using an analytic cost model based on the assumption of uniform object distribution, and then, verify the cost model through experiments using the multilevel grid file as the two-dimensional index. We further perform experiments with nonuniform object distributions. The experiments show that our proposed method builds optimal class index structures in terms of the total number of page accesses for given the precollected usage pattern regardless of query types and object distributions. (C) 2001 Elsevier Science B.V. All rights reserved.
The integration of object-oriented programming concepts with databases is one of the most significant advances in the evolution of database systems. Many aspects of such a combination have been studied, but there are ...
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The integration of object-oriented programming concepts with databases is one of the most significant advances in the evolution of database systems. Many aspects of such a combination have been studied, but there are few models to provide security for this richly structured information. We develop here an authorization model for object-oriented databases. This model consists of a set of policies, a structure for authorization rules, and algorithms to evaluate access requests against the authorization rules. User access policies are based on the concept of inherited authorization applied along the class structure hierarchy. We propose also a set of administrative policies that allow the control of user access and its decentralization. Finally, we study the effect of class structuring changes on authorization.
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