The paper is concerned with a project of data integration system designed for work in the Linked open Data space. A system architecture is suggested, and basic principles of its functioning are discussed. For data int...
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The paper is concerned with a project of data integration system designed for work in the Linked open Data space. A system architecture is suggested, and basic principles of its functioning are discussed. For data integration, it is proposed to use a combined approach based on Linked Data sets. The system can be applied for integration of data from numerous autonomous sources, between which sufficiently stable links may be identified.
In today\'s enterprise software applications, the database plays an important role. Hence, the database access tier becomes a vital component. Luckily there are many libraries, such as ODBC, JDBC, ADO, and the lik...
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In today\'s enterprise software applications, the database plays an important role. Hence, the database access tier becomes a vital component. Luckily there are many libraries, such as ODBC, JDBC, ADO, and the like, that simplify implementation. Nonetheless, finding suitable design patterns and implementing them involves the tedious task of writing domain-specific access classes. This is still the responsibility of developers. Moreover, a considerable amount of time needs to be spent maintaining this layer when the schema is not static, but continues to evolve, especially when the database schema contains a large number of tables. In this article, we present techniques for automating this process. In doing so, we introduce a lightweight tool that you can use to generate the access layer from a template that can be customized to the various access libraries.
This paper presents a learning database system that can accommodate malfunction observations. Consequently, such observations may be expressed in structured patterns to support network planing which is one of the impo...
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This paper presents a learning database system that can accommodate malfunction observations. Consequently, such observations may be expressed in structured patterns to support network planing which is one of the important network management functions. The underlying system monitors the network protocol tables in order to discover interesting patterns. To achieve this purpose two learning techniques are used. The first technique is empirical and it focuses on data samples by selecting specific fields and subsets of records using structured query language (SQL). Then data abstraction is carried out and interesting characteristics are extracted. The second technique exploits an explanation-based learning (EBL) procedure to obtain operational rules. In this case the domain (network) knowledge is formally expressed and only one training example is analyzed in terms of this knowledge. Thus, the system is capable of discovering various operational patterns, provide sensible advices, and support the network planning activity. Since the monitoring database utilizes a relational model, an integrated computer-aided software engineering (I-CASE) is used throughout the requirement identification, analysis and design phases. Accordingly, the quality of the database system as an engineering product has been achieved. Moreover, the open database connectivity (ODBC) approach is employed in order to provide an efficient interface that allows a client application to access a variety of distributed data sources in addition to its local database. (C) 2001 Elsevier Science Inc. All rights reserved.
The conventional utility billing system suffers from the inefficiency of utility provider's workforce deployment. Apart from the financial cost issue, unnecessary workforce deployment will result in an extensive p...
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