Michael L. Brodie – författare
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4 produkter
4 produkter
Häftad, Engelska, 2011
556 kr
Skickas inom 10-15 vardagar
Current experimental systems in industry, government, and the military take advantage of knowledge-based processing. For example, the Defense Advanced Research Projects Agency (DARPA), and the United States Geological Survey (USGS) are supporting the develop ment of information systems that contain diverse, vast, and growing repositories of data (e.g., vast databases storing geographic informa tion). These systems require powerful reasoning capabilities and pro cessing such as data processing, communications, and multidisciplinary of such systems will scientific analysis. The number and importance grow significantly in the near future. Many of these systems are severely limited by current knowledge base and database systems technology. Currently, knowledge-based system technology lacks the means to provide efficient and robust knowledge bases, while database system technology lacks knowledge representation and reasoning capabilities. The time has come to face the complex research problems that must be solved before we can design and implement real, large scale software systems that depend on knowledge-based processing. To date there has been little research directed at integrating knowledge base and database technologies. It is now imperative that such coordinated research be initiated and that it respond to the urgent need for a tech nology that will enable operational large-scale knowledge-based system applications.
Häftad, Engelska, 2018
1 134 kr
Skickas inom 5-8 vardagar
Inbunden, Engelska, 2018
1 367 kr
Skickas inom 5-8 vardagar
Häftad, Engelska, 2011
1 105 kr
Skickas inom 10-15 vardagar
After a long period of research, development, test and trial, relational database management systems are at last being marketed in force. The feedback from early installations of these systems is overwhelmingly positive. The most frequent comment by users is that productivity has been increased by a significant factor (from 5 to 20 times what it was using previous approaches). Another comment is that, in many cases, end users can now handle their own problems by direct use of the system instead of using application programmers as mediators between them and the system. As the reputation of relational systems for ease of use and enhanced productivity has grown, there has been a strong temptation for vendors of other approaches to exploit the label "relational" somewhat indiscriminately. In some cases the label is being misapplied to a whole data system; in others it is being misapplied to an interface. It is therefore worth developing criteria which database management systems (DBMSs) should have in order to be called "relational". The Relational Task Group (RTG) of the American National Standards Institute (ANSI) undertook such an effort by developing a characterization of RDBMSs and analyzing fourteen DBMSs per this characterization. The result of this work is presented in this book. The conclusions of the RTG are in agreement with my view that a DBMS should not be called "relational" unless it satisfies at least the following conditions: 1. All information in the database is represented as values in tables.